{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41429574", "kind": "science-record", "revision": 2, "content_hash": "sha256:7b35629c0f0be53c59a444910099022389649b212d721ace584cb76e71a7d94e", "created_at": "2026-11-01T20:31:25Z", "updated_at": "2026-11-01T21:36:12Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "scSurv: a deep generative model for single-cell survival analysis.", "doi": "10.1093/bioinformatics/btaf671", "pmid": "41429574", "authors": ["Chikara Mizukoshi", "Yasuhiro Kojima", "Shuto Hayashi", "Ko Abe", "Daisuke Kasugai", "Teppei Shimamura"], "journal": "Bioinformatics (Oxford, England)", "year": 2026, "abstract": "MOTIVATION: Single-cell omics analysis has unveiled the heterogeneity of various cell types within tumors. However, no methodology currently reveals how this heterogeneity influences cancer patient survival at single-cell resolution. Here, we introduce scSurv, combining a Cox proportional hazards model with a deep generative model of single-cell transcriptome, to estimate individual cellular contributions to clinical outcomes.\nRESULTS: The accuracy of scSurv was validated using both simulated and real datasets. This method identifies cells associated with favorable or adverse prognoses and extracts genes correlated with their contribution levels. In melanoma, scSurv reproduces known prognostic macrophage classifications and facilitates hazard mapping through spatial transcriptomics in renal cell carcinoma. We also identified genes consistently associated with prognosis across multiple cancers and demonstrated the applicability of this method to infectious diseases. scSurv is a novel framework for quantifying the heterogeneity of individual cellular effects on clinical outcomes.\nAVAILABILITY: The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054).", "claims": [{"id": "claim-method", "statement": "Here, we introduce scSurv, combining a Cox proportional hazards model with a deep generative model of single-cell transcriptome, to estimate individual cellular contributions to clinical outcomes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41429574", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Here, we introduce scSurv, combining a Cox proportional hazards model with a deep generative model of single-cell transcriptome, to estimate individual cellular contributions to clinical outcomes."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41429574", "locator": "sections[21] \"Data availability\" paragraph 2", "quote": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:41429574"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:E-MTAB-11948"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:E-MTAB-11948"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:41429574", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1093/bioinformatics/btaf671", "sha256": "sha256:5da55b2a7dac11a9ffe76b2c0a6dd48c3a8d3c7142c6efe70b230f1df9191337", "bytes": 42627, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1093/bioinformatics/btaf671", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12797213", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:E-MTAB-11948", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=E-MTAB-11948", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "E-MTAB-11948", "version": null, "note": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "access_statement_kind": "data_availability_statement", "sample_accessions": [], "sample_count": null, "group_sizes": null, "group_sizes_basis": null, "platform": null, "taxon": null, "title": null, "resolution_checked_at": "2026-11-01T20:16:19Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:E-MTAB-8107", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=E-MTAB-8107", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "E-MTAB-8107", "version": null, "note": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "access_statement_kind": "data_availability_statement", "sample_accessions": [], "sample_count": null, "group_sizes": null, "group_sizes_basis": null, "platform": null, "taxon": null, "title": null, "resolution_checked_at": "2026-11-01T19:09:51Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE115978", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE115978", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE115978", "version": null, "note": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM3197115", "GSM3197116", "GSM3197117", "GSM3197118", "GSM3197119", "GSM3197120", "GSM3197121", "GSM3197122", "GSM3197123", "GSM3197124", "GSM3197125", "GSM3197126", "GSM3197127", "GSM3197128", "GSM3197129", "GSM3197130", "GSM3197131", "GSM3197132", "GSM3197133", "GSM3197134", "GSM3197135", "GSM3197136", "GSM3197137", "GSM3197138", "GSM3197139", "GSM3197140", "GSM3197141", "GSM3197142", "GSM3197143", "GSM3197144", "GSM3197145", "GSM3197146", "GSM3197147", "GSM3197148", "GSM3197149", "GSM3197150", "GSM3197151", "GSM3197152", "GSM3197153", "GSM3197154", "GSM3197155", "GSM3197156", "GSM3197157", "GSM3197158", "GSM3197159", "GSM3197160", "GSM3197161", "GSM3197162", "GSM3197163", "GSM3197164", "GSM3197165", "GSM3197166", "GSM3197167", 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"GSM3197452", "GSM3197453", "GSM3197454", "GSM3197455", "GSM3197456", "GSM3197457", "GSM3197458", "GSM3197459", "GSM3197460", "GSM3197461", "GSM3197462", "GSM3197463", "GSM3197464", "GSM3197465", "GSM3197466", "GSM3197467", "GSM3197468", "GSM3197469", "GSM3197470", "GSM3197471", "GSM3197472", "GSM3197473", "GSM3197474", "GSM3197475", "GSM3197476", "GSM3197477", "GSM3197478", "GSM3197479", "GSM3197480", "GSM3197481", "GSM3197482", "GSM3197483", "GSM3197484", "GSM3197485", "GSM3197486", "GSM3197487", "GSM3197488", "GSM3197489", "GSM3197490", "GSM3197491", "GSM3197492", "GSM3197493", "GSM3197494", "GSM3197495", "GSM3197496", "GSM3197497", "GSM3197498", "GSM3197499", "GSM3197500", "GSM3197501", "GSM3197502", "GSM3197503", "GSM3197504", "GSM3197505", "GSM3197506", "GSM3197507", "GSM3197508", "GSM3197509", "GSM3197510", "GSM3197511", "GSM3197512", "GSM3197513", "GSM3197514", "GSM3197515", "GSM3197516", "GSM3197517", "GSM3197518", "GSM3197519", "GSM3197520", "GSM3197521", "GSM3197522", "GSM3197523", "GSM3197524", "GSM3197525", "GSM3197526", "GSM3197527", "GSM3197528", "GSM3197529", "GSM3197530", "GSM3197531", "GSM3197532", "GSM3197533", "GSM3197534", "GSM3197535", "GSM3197536", "GSM3197537", "GSM3197538", "GSM3197539", "GSM3197540", "GSM3197541", "GSM3197542", "GSM3197543", "GSM3197544", "GSM3197545", "GSM3197546", "GSM3197547", "GSM3197548", "GSM3197549", "GSM3197550", "GSM3197551", "GSM3197552", "GSM3197553", "GSM3197554", "GSM3197555", "GSM3197556", "GSM3197557", "GSM3197558", "GSM3197559", "GSM3197560", "GSM3197561", "GSM3197562", "GSM3197563", "GSM3197564", "GSM3197565", "GSM3197566", "GSM3197567", "GSM3197568", "GSM3197569", "GSM3197570", "GSM3197571", "GSM3197572", "GSM3197573", "GSM3197574", "GSM3197575", "GSM3197576", "GSM3197577", "GSM3197578", "GSM3197579", "GSM3197580", "GSM3197581", "GSM3197582", "GSM3197583", "GSM3197584", "GSM3197585", "GSM3197586", "GSM3197587", "GSM3197588", "GSM3197589", "GSM3197590", "GSM3197591", "GSM3197592", "GSM3197593", "GSM3197594", "GSM3197595", "GSM3197596", "GSM3197597", "GSM3197598", "GSM3197599", "GSM3197600", "GSM3197601", "GSM3197602", "GSM3197603", "GSM3197604", "GSM3197605", "GSM3197606", "GSM3197607", "GSM3197608", "GSM3197609", "GSM3197610", "GSM3197611", "GSM3197612", "GSM3197613", "GSM3197614", "GSM3197615", "GSM3197616", "GSM3197617", "GSM3197618", "GSM3197619", "GSM3197620", "GSM3197621", "GSM3197622", "GSM3197623", "GSM3197624", "GSM3197625", "GSM3197626", "GSM3197627", "GSM3197628", "GSM3197629", "GSM3197630", "GSM3197631", "GSM3197632", "GSM3197633", "GSM3197634", "GSM3197635", "GSM3197636", "GSM3197637", "GSM3197638", "GSM3197639", "GSM3197640", "GSM3197641", "GSM3197642", "GSM3197643", "GSM3197644", "GSM3197645", "GSM3197646", "GSM3197647", "GSM3197648", "GSM3197649", "GSM3197650", "GSM3197651", "GSM3197652", "GSM3197653", "GSM3197654", "GSM3197655", "GSM3197656", "GSM3197657", "GSM3197658", "GSM3197659", "GSM3197660", "GSM3197661", "GSM3197662", "GSM3197663", "GSM3197664", "GSM3197665", "GSM3197666", "GSM3197667", "GSM3197668", "GSM3197669", "GSM3197670", "GSM3197671", "GSM3197672", "GSM3197673", "GSM3197674", "GSM3197675", "GSM3197676", "GSM3197677", "GSM3197678", "GSM3197679", "GSM3197680", "GSM3197681", "GSM3197682", "GSM3197683", "GSM3197684", "GSM3197685", "GSM3197686", "GSM3197687", "GSM3197688", "GSM3197689", "GSM3197690", "GSM3197691", "GSM3197692", "GSM3197693", "GSM3197694", "GSM3197695", "GSM3197696", "GSM3197697", "GSM3197698", "GSM3197699", "GSM3197700", "GSM3197701", "GSM3197702", "GSM3197703", "GSM3197704", "GSM3197705", "GSM3197706", "GSM3197707", "GSM3197708", "GSM3197709", "GSM3197710", "GSM3197711", "GSM3197712", "GSM3197713", "GSM3197714", "GSM3197715", "GSM3197716", "GSM3197717", "GSM3197718", "GSM3197719", "GSM3197720", "GSM3197721", "GSM3197722", "GSM3197723", "GSM3197724", "GSM3197725", "GSM3197726", "GSM3197727", "GSM3197728", "GSM3197729", "GSM3197730", "GSM3197731", "GSM3197732", "GSM3197733", "GSM3197734", "GSM3197735", "GSM3197736", "GSM3197737", "GSM3197738", "GSM3197739", "GSM3197740", "GSM3197741", "GSM3197742", "GSM3197743", "GSM3197744", "GSM3197745", "GSM3197746", "GSM3197747", "GSM3197748", "GSM3197749", "GSM3197750", "GSM3197751", "GSM3197752", "GSM3197753", "GSM3197754", "GSM3197755", "GSM3197756", "GSM3197757", "GSM3197758", "GSM3197759", "GSM3197760", "GSM3197761", "GSM3197762", "GSM3197763", "GSM3197764", "GSM3197765", "GSM3197766", "GSM3197767", "GSM3197768", "GSM3197769", "GSM3197770", "GSM3197771", "GSM3197772", "GSM3197773", "GSM3197774", "GSM3197775", "GSM3197776", "GSM3197777", "GSM3197778", "GSM3197779", "GSM3197780", "GSM3197781", "GSM3197782", "GSM3197783", "GSM3197784", "GSM3197785", "GSM3197786", "GSM3197787", "GSM3197788", "GSM3197789", "GSM3197790", "GSM3197791", "GSM3197792", "GSM3197793", "GSM3197794", "GSM3197795", "GSM3197796", "GSM3197797", "GSM3197798", "GSM3197799", "GSM3197800", "GSM3197801", "GSM3197802", "GSM3197803", "GSM3197804", "GSM3197805", "GSM3197806", "GSM3197807", "GSM3197808", "GSM3197809", "GSM3197810", "GSM3197811", "GSM3197812", "GSM3197813", "GSM3197814", "GSM3197815", "GSM3197816", "GSM3197817", "GSM3197818", "GSM3197819", "GSM3197820", "GSM3197821", "GSM3197822", "GSM3197823", "GSM3197824", "GSM3197825", "GSM3197826", "GSM3197827", "GSM3197828", "GSM3197829", "GSM3197830", "GSM3197831", "GSM3197832", "GSM3197833", "GSM3197834", "GSM3197835", "GSM3197836", "GSM3197837", "GSM3197838", "GSM3197839", "GSM3197840", "GSM3197841", "GSM3197842", "GSM3197843", "GSM3197844", "GSM3197845", "GSM3197846", "GSM3197847", "GSM3197848", "GSM3197849", "GSM3197850", "GSM3197851", "GSM3197852", "GSM3197853", "GSM3197854", "GSM3197855", "GSM3197856", "GSM3197857", "GSM3197858", "GSM3197859", "GSM3197860", "GSM3197861", "GSM3197862", "GSM3197863", "GSM3197864", "GSM3197865", "GSM3197866", "GSM3197867", "GSM3197868", "GSM3197869", "GSM3197870", "GSM3197871", "GSM3197872", "GSM3197873", "GSM3197874", "GSM3197875", "GSM3197876", "GSM3197877", "GSM3197878", "GSM3197879", "GSM3197880", "GSM3197881", "GSM3197882", "GSM3197883", "GSM3197884", "GSM3197885", "GSM3197886", "GSM3197887", "GSM3197888", "GSM3197889", "GSM3197890", "GSM3197891", "GSM3197892", "GSM3197893", "GSM3197894", "GSM3197895", "GSM3197896", "GSM3197897", "GSM3197898", "GSM3197899", "GSM3197900", "GSM3197901", "GSM3197902", "GSM3197903", "GSM3197904", "GSM3197905", "GSM3197906", "GSM3197907", "GSM3197908", "GSM3197909", "GSM3197910", "GSM3197911", "GSM3197912", "GSM3197913", "GSM3197914", "GSM3197915", "GSM3197916", "GSM3197917", "GSM3197918", "GSM3197919", "GSM3197920", "GSM3197921", "GSM3197922", "GSM3197923", "GSM3197924", "GSM3197925", "GSM3197926", "GSM3197927", "GSM3197928", "GSM3197929", "GSM3197930", "GSM3197931", "GSM3197932", "GSM3197933", "GSM3197934", "GSM3197935", "GSM3197936", "GSM3197937", "GSM3197938", "GSM3197939", "GSM3197940", "GSM3197941", "GSM3197942", "GSM3197943", "GSM3197944", "GSM3197945", "GSM3197946", "GSM3197947", "GSM3197948", "GSM3197949", "GSM3197950", "GSM3197951", "GSM3197952", "GSM3197953", "GSM3197954", "GSM3197955", "GSM3197956", "GSM3197957", "GSM3197958", "GSM3197959", "GSM3197960", "GSM3197961", "GSM3197962", "GSM3197963", "GSM3197964", "GSM3197965", "GSM3197966", "GSM3197967", "GSM3197968", "GSM3197969", "GSM3197970", "GSM3197971", "GSM3197972", "GSM3197973", "GSM3197974", "GSM3197975", "GSM3197976", "GSM3197977", "GSM3197978", "GSM3197979", "GSM3197980", "GSM3197981", "GSM3197982", "GSM3197983", "GSM3197984", "GSM3197985", "GSM3197986", "GSM3197987", "GSM3197988", "GSM3197989", "GSM3197990", "GSM3197991", "GSM3197992", "GSM3197993", "GSM3197994", "GSM3197995", "GSM3197996", "GSM3197997", "GSM3197998", "GSM3197999", "GSM3198000", "GSM3198001", "GSM3198002", "GSM3198003", "GSM3198004", "GSM3198005", "GSM3198006", "GSM3198007", "GSM3198008", "GSM3198009", "GSM3198010", "GSM3198011", "GSM3198012", "GSM3198013", "GSM3198014", "GSM3198015", "GSM3198016", "GSM3198017", "GSM3198018", "GSM3198019", "GSM3198020", "GSM3198021", "GSM3198022", "GSM3198023", "GSM3198024", "GSM3198025", "GSM3198026", "GSM3198027", "GSM3198028", "GSM3198029", "GSM3198030", "GSM3198031", "GSM3198032", "GSM3198033", "GSM3198034", "GSM3198035", "GSM3198036", "GSM3198037", "GSM3198038", "GSM3198039", "GSM3198040", "GSM3198041", "GSM3198042", "GSM3198043", "GSM3198044", "GSM3198045", "GSM3198046", "GSM3198047", "GSM3198048", "GSM3198049", "GSM3198050", "GSM3198051", "GSM3198052", "GSM3198053", "GSM3198054", "GSM3198055", "GSM3198056", "GSM3198057", "GSM3198058", "GSM3198059", "GSM3198060", "GSM3198061", "GSM3198062", "GSM3198063", "GSM3198064", "GSM3198065", "GSM3198066", "GSM3198067", "GSM3198068", "GSM3198069", "GSM3198070", "GSM3198071", "GSM3198072", "GSM3198073", "GSM3198074", "GSM3198075", "GSM3198076", "GSM3198077", "GSM3198078", "GSM3198079", "GSM3198080", "GSM3198081", "GSM3198082", "GSM3198083", "GSM3198084", "GSM3198085", "GSM3198086", "GSM3198087", "GSM3198088", "GSM3198089", "GSM3198090", "GSM3198091", "GSM3198092", "GSM3198093", "GSM3198094", "GSM3198095", "GSM3198096", "GSM3198097", "GSM3198098", "GSM3198099", "GSM3198100", "GSM3198101", "GSM3198102", "GSM3198103", "GSM3198104", "GSM3198105", "GSM3198106", "GSM3198107", "GSM3198108", "GSM3198109", "GSM3198110", "GSM3198111", "GSM3198112", "GSM3198113", "GSM3198114", "GSM3198115", "GSM3198116", "GSM3198117", "GSM3198118", "GSM3198119", "GSM3198120", "GSM3198121", "GSM3198122", "GSM3198123", "GSM3198124", "GSM3198125", "GSM3198126", "GSM3198127", "GSM3198128", "GSM3198129", "GSM3198130", "GSM3198131", "GSM3198132", "GSM3198133", "GSM3198134", "GSM3198135", "GSM3198136", "GSM3198137", "GSM3198138", "GSM3198139", "GSM3198140", "GSM3198141", "GSM3198142", "GSM3198143", "GSM3198144", "GSM3198145", "GSM3198146", "GSM3198147", "GSM3198148", "GSM3198149", "GSM3198150", "GSM3198151", "GSM3198152", "GSM3198153", "GSM3198154", "GSM3198155", "GSM3198156", "GSM3198157", "GSM3198158", "GSM3198159", "GSM3198160", "GSM3198161", "GSM3198162", "GSM3198163", "GSM3198164", "GSM3198165", "GSM3198166", "GSM3198167", "GSM3198168", "GSM3198169", "GSM3198170", "GSM3198171", "GSM3198172", "GSM3198173", "GSM3198174", "GSM3198175", "GSM3198176", "GSM3198177", "GSM3198178", "GSM3198179", "GSM3198180", "GSM3198181", "GSM3198182", "GSM3198183", "GSM3198184", "GSM3198185", "GSM3198186", "GSM3198187", "GSM3198188", "GSM3198189", "GSM3198190", "GSM3198191", "GSM3198192", "GSM3198193", "GSM3198194", "GSM3198195", "GSM3198196", "GSM3198197", "GSM3198198", "GSM3198199", "GSM3198200", "GSM3198201", "GSM3198202", "GSM3198203", "GSM3198204", "GSM3198205", "GSM3198206", "GSM3198207", "GSM3198208", "GSM3198209", "GSM3198210", "GSM3198211", "GSM3198212", "GSM3198213", "GSM3198214", "GSM3198215", "GSM3198216", "GSM3198217", "GSM3198218", "GSM3198219", "GSM3198220", "GSM3198221", "GSM3198222", "GSM3198223", "GSM3198224", "GSM3198225", "GSM3198226", "GSM3198227", "GSM3198228", "GSM3198229", "GSM3198230", "GSM3198231", "GSM3198232", "GSM3198233", "GSM3198234", "GSM3198235", "GSM3198236", "GSM3198237", "GSM3198238", "GSM3198239", "GSM3198240", "GSM3198241", "GSM3198242", "GSM3198243", "GSM3198244", "GSM3198245", "GSM3198246", "GSM3198247", "GSM3198248", "GSM3198249", "GSM3198250", "GSM3198251", "GSM3198252", "GSM3198253", "GSM3198254", "GSM3198255", "GSM3198256", "GSM3198257", "GSM3198258", "GSM3198259", "GSM3198260", "GSM3198261", "GSM3198262", "GSM3198263", "GSM3198264", "GSM3198265", "GSM3198266", "GSM3198267", "GSM3198268", "GSM3198269", "GSM3198270", "GSM3198271", "GSM3198272", "GSM3198273", "GSM3198274", "GSM3198275", "GSM3198276", "GSM3198277", "GSM3198278", "GSM3198279", "GSM3198280", "GSM3198281", "GSM3198282", "GSM3198283", "GSM3198284", "GSM3198285", "GSM3198286", "GSM3198287", "GSM3198288", "GSM3198289", "GSM3198290", "GSM3198291", "GSM3198292", "GSM3198293", "GSM3198294", "GSM3198295", "GSM3198296", "GSM3198297", "GSM3198298", "GSM3198299", "GSM3198300", "GSM3198301", "GSM3198302", "GSM3198303", "GSM3198304", "GSM3198305", "GSM3198306", "GSM3198307", "GSM3198308", "GSM3198309", "GSM3198310", "GSM3198311", "GSM3198312", "GSM3198313", "GSM3198314", "GSM3198315", "GSM3198316", "GSM3198317", "GSM3198318", "GSM3198319", "GSM3198320", "GSM3198321", "GSM3198322", "GSM3198323", "GSM3198324", "GSM3198325", "GSM3198326", "GSM3198327", "GSM3198328", "GSM3198329", "GSM3198330", "GSM3198331", "GSM3198332", "GSM3198333", "GSM3198334", "GSM3198335", "GSM3198336", "GSM3198337", "GSM3198338", "GSM3198339", "GSM3198340", "GSM3198341", "GSM3198342", "GSM3198343", "GSM3198344", "GSM3198345", "GSM3198346", "GSM3198347", "GSM3198348", "GSM3198349", "GSM3198350", "GSM3198351", "GSM3198352", "GSM3198353", "GSM3198354", "GSM3198355", "GSM3198356", "GSM3198357", "GSM3198358", "GSM3198359", "GSM3198360", "GSM3198361", "GSM3198362", "GSM3198363", "GSM3198364", "GSM3198365", "GSM3198366", "GSM3198367", "GSM3198368", "GSM3198369", "GSM3198370", "GSM3198371", "GSM3198372", "GSM3198373", "GSM3198374", "GSM3198375", "GSM3198376", "GSM3198377", "GSM3198378", "GSM3198379", "GSM3198380", "GSM3198381", "GSM3198382", "GSM3198383", "GSM3198384", "GSM3198385", "GSM3198386", "GSM3198387", "GSM3198388", "GSM3198389", "GSM3198390", "GSM3198391", "GSM3198392", "GSM3198393", "GSM3198394", "GSM3198395", "GSM3198396", "GSM3198397", "GSM3198398", "GSM3198399", "GSM3198400", "GSM3198401", "GSM3198402", "GSM3198403", "GSM3198404", "GSM3198405", "GSM3198406", "GSM3198407", "GSM3198408", "GSM3198409", "GSM3198410", "GSM3198411", "GSM3198412", "GSM3198413", "GSM3198414", "GSM3198415", "GSM3198416", "GSM3198417", "GSM3198418", "GSM3198419", "GSM3198420", "GSM3198421", "GSM3198422", "GSM3198423", "GSM3198424", "GSM3198425", "GSM3198426", "GSM3198427", "GSM3198428", "GSM3198429", "GSM3198430", "GSM3198431", "GSM3198432", "GSM3198433", "GSM3198434", "GSM3198435", "GSM3198436", "GSM3198437", "GSM3198438", "GSM3198439", "GSM3198440", "GSM3198441", "GSM3198442", "GSM3198443", "GSM3198444", "GSM3198445", "GSM3198446", "GSM3198447", "GSM3198448", "GSM3198449", "GSM3198450", "GSM3198451", "GSM3198452", "GSM3198453", "GSM3198454", "GSM3198455", "GSM3198456", "GSM3198457", "GSM3198458", "GSM3198459", "GSM3198460", "GSM3198461", "GSM3198462", "GSM3198463", "GSM3198464", "GSM3198465", "GSM3198466", "GSM3198467", "GSM3198468", "GSM3198469", "GSM3198470", "GSM3198471", "GSM3198472", "GSM3198473", "GSM3198474", "GSM3198475", "GSM3198476", "GSM3198477", "GSM3198478", "GSM3198479", "GSM3198480", "GSM3198481", "GSM3198482", "GSM3198483", "GSM3198484", "GSM3198485", "GSM3198486", "GSM3198487", "GSM3198488", "GSM3198489", "GSM3198490", "GSM3198491", "GSM3198492", "GSM3198493", "GSM3198494", "GSM3198495", "GSM3198496", "GSM3198497", "GSM3198498", "GSM3198499", "GSM3198500", "GSM3198501", "GSM3198502", "GSM3198503", "GSM3198504", "GSM3198505", "GSM3198506", "GSM3198507", "GSM3198508", "GSM3198509", "GSM3198510", "GSM3198511", "GSM3198512", "GSM3198513", "GSM3198514", "GSM3198515", "GSM3198516", "GSM3198517", "GSM3198518", "GSM3198519", "GSM3198520", "GSM3198521", "GSM3198522", "GSM3198523", "GSM3198524", "GSM3198525", "GSM3198526", "GSM3198527", "GSM3198528", "GSM3198529", "GSM3198530", "GSM3198531", "GSM3198532", "GSM3198533", "GSM3198534", "GSM3198535", "GSM3198536", "GSM3198537", "GSM3198538", "GSM3198539", "GSM3198540", "GSM3198541", "GSM3198542", "GSM3198543", "GSM3198544", "GSM3198545", "GSM3198546", "GSM3198547", "GSM3198548", "GSM3198549", "GSM3198550", "GSM3198551", "GSM3198552", "GSM3198553", "GSM3198554", "GSM3198555", "GSM3198556", "GSM3198557", "GSM3198558", "GSM3198559", "GSM3198560", "GSM3198561", "GSM3198562", "GSM3198563", "GSM3198564", "GSM3198565", "GSM3198566", "GSM3198567", "GSM3198568", "GSM3198569", "GSM3198570", "GSM3198571", "GSM3198572", "GSM3198573", "GSM3198574", "GSM3198575", "GSM3198576", "GSM3198577", "GSM3198578", "GSM3198579", "GSM3198580", "GSM3198581", "GSM3198582", "GSM3198583", "GSM3198584", "GSM3198585", "GSM3198586", "GSM3198587", "GSM3198588", "GSM3198589", "GSM3198590", "GSM3198591", "GSM3198592", "GSM3198593", "GSM3198594", "GSM3198595", "GSM3198596", "GSM3198597", "GSM3198598", "GSM3198599", "GSM3198600", "GSM3198601", "GSM3198602", "GSM3198603", "GSM3198604", "GSM3198605", "GSM3198606", "GSM3198607", "GSM3198608", "GSM3198609", "GSM3198610", "GSM3198611", "GSM3198612", "GSM3198613", "GSM3198614", "GSM3198615", "GSM3198616", "GSM3198617", "GSM3198618", "GSM3198619", "GSM3198620", "GSM3198621", "GSM3198622", "GSM3198623", "GSM3198624", "GSM3198625", "GSM3198626", "GSM3198627", "GSM3198628", "GSM3198629", "GSM3198630", "GSM3198631", "GSM3198632", "GSM3198633", "GSM3198634", "GSM3198635", "GSM3198636", "GSM3198637", "GSM3198638", "GSM3198639", "GSM3198640", "GSM3198641", "GSM3198642", "GSM3198643", "GSM3198644", "GSM3198645", "GSM3198646", "GSM3198647", "GSM3198648", "GSM3198649", "GSM3198650", "GSM3198651", "GSM3198652", "GSM3198653", "GSM3198654", "GSM3198655", "GSM3198656", "GSM3198657", "GSM3198658", 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"GSM3198730", "GSM3198731", "GSM3198732", "GSM3198733", "GSM3198734", "GSM3198735", "GSM3198736", "GSM3198737", "GSM3198738", "GSM3198739", "GSM3198740", "GSM3198741", "GSM3198742", "GSM3198743", "GSM3198744", "GSM3198745", "GSM3198746", "GSM3198747", "GSM3198748", "GSM3198749", "GSM3198750", "GSM3198751", "GSM3198752", "GSM3198753", "GSM3198754", "GSM3198755", "GSM3198756", "GSM3198757", "GSM3198758", "GSM3198759", "GSM3198760", "GSM3198761", "GSM3198762", "GSM3198763", "GSM3198764", "GSM3198765", "GSM3198766", "GSM3198767", "GSM3198768", "GSM3198769", "GSM3198770", "GSM3198771", "GSM3198772", "GSM3198773", "GSM3198774", "GSM3198775", "GSM3198776", "GSM3198777", "GSM3198778", "GSM3198779", "GSM3198780", "GSM3198781", "GSM3198782", "GSM3198783", "GSM3198784", "GSM3198785", "GSM3198786", "GSM3198787", "GSM3198788", "GSM3198789", "GSM3198790", "GSM3198791", "GSM3198792", "GSM3198793", "GSM3198794", "GSM3198795", "GSM3198796", "GSM3198797", "GSM3198798", "GSM3198799", "GSM3198800", 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"GSM3198943", "GSM3198944", "GSM3198945", "GSM3198946", "GSM3198947", "GSM3198948", "GSM3198949", "GSM3198950", "GSM3198951", "GSM3198952", "GSM3198953", "GSM3198954", "GSM3198955", "GSM3198956", "GSM3198957", "GSM3198958", "GSM3198959", "GSM3198960", "GSM3198961", "GSM3198962", "GSM3198963", "GSM3198964", "GSM3198965", "GSM3198966", "GSM3198967", "GSM3198968", "GSM3198969", "GSM3198970", "GSM3198971", "GSM3198972", "GSM3198973", "GSM3198974", "GSM3198975", "GSM3198976", "GSM3198977", "GSM3198978", "GSM3198979", "GSM3198980", "GSM3198981", "GSM3198982", "GSM3198983", "GSM3198984", "GSM3198985", "GSM3198986", "GSM3198987", "GSM3198988", "GSM3198989", "GSM3198990", "GSM3198991", "GSM3198992", "GSM3198993", "GSM3198994", "GSM3198995", "GSM3198996", "GSM3198997", "GSM3198998", "GSM3198999", "GSM3199000", "GSM3199001", "GSM3199002", "GSM3199003", "GSM3199004", "GSM3199005", "GSM3199006", "GSM3199007", "GSM3199008", "GSM3199009", "GSM3199010", "GSM3199011", "GSM3199012", "GSM3199013", "GSM3199014", "GSM3199015", "GSM3199016", "GSM3199017", "GSM3199018", "GSM3199019", "GSM3199020", "GSM3199021", "GSM3199022", "GSM3199023", "GSM3199024", "GSM3199025", "GSM3199026", "GSM3199027", "GSM3199028", "GSM3199029", "GSM3199030", "GSM3199031", "GSM3199032", "GSM3199033", "GSM3199034", "GSM3199035", "GSM3199036", "GSM3199037", "GSM3199038", "GSM3199039", "GSM3199040", "GSM3199041", "GSM3199042", "GSM3199043", "GSM3199044", "GSM3199045", "GSM3199046", "GSM3199047", "GSM3199048", "GSM3199049", "GSM3199050", "GSM3199051", "GSM3199052", "GSM3199053", "GSM3199054", "GSM3199055", "GSM3199056", "GSM3199057", "GSM3199058", "GSM3199059", "GSM3199060", "GSM3199061", "GSM3199062", "GSM3199063", "GSM3199064", "GSM3199065", "GSM3199066", "GSM3199067", "GSM3199068", "GSM3199069", "GSM3199070", "GSM3199071", "GSM3199072", "GSM3199073", "GSM3199074", "GSM3199075", "GSM3199076", "GSM3199077", "GSM3199078", "GSM3199079", "GSM3199080", "GSM3199081", "GSM3199082", "GSM3199083", "GSM3199084", "GSM3199085", "GSM3199086", "GSM3199087", "GSM3199088", "GSM3199089", "GSM3199090", "GSM3199091", "GSM3199092", "GSM3199093", "GSM3199094", "GSM3199095", "GSM3199096", "GSM3199097", "GSM3199098", "GSM3199099", "GSM3199100", "GSM3199101", "GSM3199102", "GSM3199103", "GSM3199104", "GSM3199105", "GSM3199106", "GSM3199107", "GSM3199108", "GSM3199109", "GSM3199110", "GSM3199111", "GSM3199112", "GSM3199113", "GSM3199114", "GSM3199115", "GSM3199116", "GSM3199117", "GSM3199118", "GSM3199119", "GSM3199120", "GSM3199121", "GSM3199122", "GSM3199123", "GSM3199124", "GSM3199125", "GSM3199126", "GSM3199127", "GSM3199128", "GSM3199129", "GSM3199130", "GSM3199131", "GSM3199132", "GSM3199133", "GSM3199134", "GSM3199135", "GSM3199136", "GSM3199137", "GSM3199138", "GSM3199139", "GSM3199140", "GSM3199141", "GSM3199142", "GSM3199143", "GSM3199144", "GSM3199145", "GSM3199146", "GSM3199147", "GSM3199148", "GSM3199149", "GSM3199150", "GSM3199151", "GSM3199152", "GSM3199153", "GSM3199154", "GSM3199155", "GSM3199156", "GSM3199157", "GSM3199158", "GSM3199159", "GSM3199160", "GSM3199161", "GSM3199162", "GSM3199163", "GSM3199164", "GSM3199165", "GSM3199166", "GSM3199167", "GSM3199168", "GSM3199169", "GSM3199170", "GSM3199171", "GSM3199172", "GSM3199173", "GSM3199174", "GSM3199175", "GSM3199176", "GSM3199177", "GSM3199178", "GSM3199179", "GSM3199180", "GSM3199181", "GSM3199182", "GSM3199183", "GSM3199184", "GSM3199185", "GSM3199186", "GSM3199187", "GSM3199188", "GSM3199189", "GSM3199190", "GSM3199191", "GSM3199192", "GSM3199193", "GSM3199194", "GSM3199195", "GSM3199196", "GSM3199197", "GSM3199198", "GSM3199199", "GSM3199200", "GSM3199201", "GSM3199202", "GSM3199203", "GSM3199204", "GSM3199205", "GSM3199206", "GSM3199207", "GSM3199208", "GSM3199209", "GSM3199210", "GSM3199211", "GSM3199212", "GSM3199213", "GSM3199214", "GSM3199215", "GSM3199216", "GSM3199217", "GSM3199218", "GSM3199219", "GSM3199220", "GSM3199221", "GSM3199222", "GSM3199223", "GSM3199224", "GSM3199225", "GSM3199226", "GSM3199227", "GSM3199228", "GSM3199229", "GSM3199230", "GSM3199231", "GSM3199232", "GSM3199233", "GSM3199234", "GSM3199235", "GSM3199236", "GSM3199237", "GSM3199238", "GSM3199239", "GSM3199240", "GSM3199241", "GSM3199242", "GSM3199243", "GSM3199244", "GSM3199245", "GSM3199246", "GSM3199247", "GSM3199248", "GSM3199249", "GSM3199250", "GSM3199251", "GSM3199252", "GSM3199253", "GSM3199254", "GSM3199255", "GSM3199256", "GSM3199257", "GSM3199258", "GSM3199259", "GSM3199260", "GSM3199261", "GSM3199262", "GSM3199263", "GSM3199264", "GSM3199265", "GSM3199266", "GSM3199267", "GSM3199268", "GSM3199269", "GSM3199270", "GSM3199271", "GSM3199272", "GSM3199273", "GSM3199274", "GSM3199275", "GSM3199276", "GSM3199277", "GSM3199278", "GSM3199279", "GSM3199280", "GSM3199281", "GSM3199282", "GSM3199283", "GSM3199284", "GSM3199285", "GSM3199286", "GSM3199287", "GSM3199288", "GSM3199289", "GSM3199290", "GSM3199291", "GSM3199292", "GSM3199293", "GSM3199294", "GSM3199295", "GSM3199296", "GSM3199297", 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"GSM3200434", "GSM3200435", "GSM3200436", "GSM3200437", "GSM3200438", "GSM3200439", "GSM3200440", "GSM3200441", "GSM3200442", "GSM3200443", "GSM3200444", "GSM3200445", "GSM3200446", "GSM3200447", "GSM3200448", "GSM3200449", "GSM3200450", "GSM3200451", "GSM3200452", "GSM3200453", "GSM3200454", "GSM3200455", "GSM3200456", "GSM3200457", "GSM3200458", "GSM3200459", "GSM3200460", "GSM3200461", "GSM3200462", "GSM3200463", "GSM3200464", "GSM3200465", "GSM3200466", "GSM3200467", "GSM3200468", "GSM3200469", "GSM3200470", "GSM3200471", "GSM3200472", "GSM3200473", "GSM3200474", "GSM3200475", "GSM3200476", "GSM3200477", "GSM3200478", "GSM3200479", "GSM3200480", "GSM3200481", "GSM3200482", "GSM3200483", "GSM3200484", "GSM3200485", "GSM3200486", "GSM3200487", "GSM3200488", "GSM3200489", "GSM3200490", "GSM3200491", "GSM3200492", "GSM3200493", "GSM3200494", "GSM3200495", "GSM3200496", "GSM3200497", "GSM3200498", "GSM3200499", "GSM3200500", "GSM3200501", "GSM3200502", "GSM3200503", "GSM3200504", "GSM3200505", "GSM3200506", "GSM3200507", "GSM3200508", "GSM3200509", "GSM3200510", "GSM3200511", "GSM3200512", "GSM3200513", "GSM3200514", "GSM3200515", "GSM3200516", "GSM3200517", "GSM3200518", "GSM3200519", "GSM3200520", "GSM3200521", "GSM3200522", "GSM3200523", "GSM3200524", "GSM3200525", "GSM3200526", "GSM3200527", "GSM3200528", "GSM3200529", "GSM3200530", "GSM3200531", "GSM3200532", "GSM3200533", "GSM3200534", "GSM3200535", "GSM3200536", "GSM3200537", "GSM3200538", "GSM3200539", "GSM3200540", "GSM3200541", "GSM3200542", "GSM3200543", "GSM3200544", "GSM3200545", "GSM3200546", "GSM3200547", "GSM3200548", "GSM3200549", "GSM3200550", "GSM3200551", "GSM3200552", "GSM3200553", "GSM3200554", "GSM3200555", "GSM3200556", "GSM3200557", "GSM3200558", "GSM3200559", "GSM3200560", "GSM3200561", "GSM3200562", "GSM3200563", "GSM3200564", "GSM3200565", "GSM3200566", "GSM3200567", "GSM3200568", "GSM3200569", "GSM3200570", "GSM3200571", "GSM3200572", "GSM3200573", "GSM3200574", "GSM3200575", "GSM3200576", "GSM3200577", "GSM3200578", "GSM3200579", "GSM3200580", "GSM3200581", "GSM3200582", "GSM3200583", "GSM3200584", "GSM3200585", "GSM3200586", "GSM3200587", "GSM3200588", "GSM3200589", "GSM3200590", "GSM3200591", "GSM3200592", "GSM3200593", "GSM3200594", "GSM3200595", "GSM3200596", "GSM3200597", "GSM3200598", "GSM3200599", "GSM3200600", "GSM3200601", "GSM3200602", "GSM3200603", "GSM3200604", "GSM3200605", "GSM3200606", "GSM3200607", "GSM3200608", "GSM3200609", "GSM3200610", "GSM3200611", "GSM3200612", "GSM3200613", "GSM3200614", "GSM3200615", "GSM3200616", "GSM3200617", "GSM3200618", "GSM3200619", "GSM3200620", "GSM3200621", "GSM3200622", "GSM3200623", "GSM3200624", "GSM3200625", "GSM3200626", "GSM3200627", "GSM3200628", "GSM3200629", "GSM3200630", "GSM3200631", "GSM3200632", "GSM3200633", "GSM3200634", "GSM3200635", "GSM3200636", "GSM3200637", "GSM3200638", "GSM3200639", "GSM3200640", "GSM3200641", "GSM3200642", "GSM3200643", "GSM3200644", "GSM3200645", "GSM3200646", "GSM3200647", "GSM3200648", "GSM3200649", "GSM3200650", "GSM3200651", "GSM3200652", "GSM3200653", "GSM3200654", "GSM3200655", "GSM3200656", "GSM3200657", "GSM3200658", "GSM3200659", "GSM3200660", "GSM3200661", "GSM3200662", "GSM3200663", "GSM3200664", "GSM3200665", "GSM3200666", "GSM3200667", "GSM3200668", "GSM3200669", "GSM3200670", "GSM3200671", "GSM3200672", "GSM3200673", "GSM3200674", "GSM3200675", "GSM3200676", "GSM3200677", "GSM3200678", "GSM3200679", "GSM3200680", "GSM3200681", "GSM3200682", "GSM3200683", "GSM3200684", "GSM3200685", "GSM3200686", "GSM3200687", "GSM3200688", "GSM3200689", "GSM3200690", "GSM3200691", "GSM3200692", "GSM3200693", "GSM3200694", "GSM3200695", "GSM3200696", "GSM3200697", "GSM3200698", "GSM3200699", "GSM3200700", "GSM3200701", "GSM3200702", "GSM3200703", "GSM3200704", "GSM3200705", "GSM3200706", "GSM3200707", "GSM3200708", "GSM3200709", "GSM3200710", "GSM3200711", "GSM3200712", "GSM3200713", "GSM3200714", "GSM3200715", "GSM3200716", "GSM3200717", "GSM3200718", "GSM3200719", "GSM3200720", "GSM3200721", "GSM3200722", "GSM3200723", "GSM3200724", "GSM3200725", "GSM3200726", "GSM3200727", "GSM3200728", "GSM3200729", "GSM3200730", "GSM3200731", "GSM3200732", "GSM3200733", "GSM3200734", "GSM3200735", "GSM3200736", "GSM3200737", "GSM3200738", "GSM3200739", "GSM3200740", "GSM3200741", "GSM3200742", "GSM3200743", "GSM3200744", "GSM3200745", "GSM3200746", "GSM3200747", "GSM3200748", "GSM3200749", "GSM3200750", "GSM3200751", "GSM3200752", "GSM3200753", "GSM3200754", "GSM3200755", "GSM3200756", "GSM3200757", "GSM3200758", "GSM3200759", "GSM3200760", "GSM3200761", "GSM3200762", "GSM3200763", "GSM3200764", "GSM3200765", "GSM3200766", "GSM3200767", "GSM3200768", "GSM3200769", "GSM3200770", "GSM3200771", "GSM3200772", "GSM3200773", "GSM3200774", "GSM3200775", "GSM3200776", "GSM3200777", "GSM3200778", "GSM3200779", "GSM3200780", "GSM3200781", "GSM3200782", "GSM3200783", "GSM3200784", "GSM3200785", "GSM3200786", "GSM3200787", "GSM3200788", "GSM3200789", "GSM3200790", "GSM3200791", "GSM3200792", "GSM3200793", "GSM3200794", "GSM3200795", "GSM3200796", "GSM3200797", "GSM3200798", "GSM3200799", "GSM3200800", "GSM3200801", "GSM3200802", "GSM3200803", "GSM3200804", "GSM3200805", "GSM3200806", "GSM3200807", "GSM3200808", "GSM3200809", "GSM3200810", "GSM3200811", "GSM3200812", "GSM3200813", "GSM3200814", "GSM3200815", "GSM3200816", "GSM3200817", "GSM3200818", "GSM3200819", "GSM3200820", "GSM3200821", "GSM3200822", "GSM3200823", "GSM3200824", "GSM3200825", "GSM3200826", "GSM3200827", "GSM3200828", "GSM3200829", "GSM3200830", "GSM3200831", "GSM3200832", "GSM3200833", "GSM3200834", "GSM3200835", "GSM3200836", "GSM3200837", "GSM3200838", "GSM3200839", "GSM3200840", "GSM3200841", "GSM3200842", "GSM3200843", "GSM3200844", "GSM3200845", "GSM3200846", "GSM3200847", "GSM3200848", "GSM3200849", "GSM3200850", "GSM3200851", "GSM3200852", "GSM3200853", "GSM3200854", "GSM3200855", "GSM3200856", "GSM3200857", "GSM3200858", "GSM3200859", "GSM3200860", "GSM3200861", "GSM3200862", "GSM3200863", "GSM3200864", "GSM3200865", "GSM3200866", "GSM3200867", "GSM3200868", "GSM3200869", "GSM3200870", "GSM3200871", "GSM3200872", "GSM3200873", "GSM3200874", "GSM3200875", "GSM3200876", "GSM3200877", "GSM3200878", "GSM3200879", "GSM3200880", "GSM3200881", "GSM3200882", "GSM3200883", "GSM3200884", "GSM3200885", "GSM3200886", "GSM3200887", "GSM3200888", "GSM3200889", "GSM3200890", "GSM3200891", "GSM3200892", "GSM3200893", "GSM3200894", "GSM3200895", "GSM3200896", "GSM3200897", "GSM3200898", "GSM3200899", "GSM3200900", "GSM3200901", "GSM3200902", "GSM3200903", "GSM3200904", "GSM3200905", "GSM3200906", "GSM3200907", "GSM3200908", "GSM3200909", "GSM3200910", "GSM3200911", "GSM3200912", "GSM3200913", "GSM3200914", "GSM3200915", "GSM3200916", "GSM3200917", "GSM3200918", "GSM3200919", "GSM3200920", "GSM3200921", "GSM3200922", "GSM3200923", "GSM3200924", "GSM3200925", "GSM3200926", "GSM3200927", "GSM3200928", "GSM3200929", "GSM3200930", "GSM3200931", "GSM3200932", "GSM3200933", "GSM3200934", "GSM3200935", "GSM3200936", "GSM3200937", "GSM3200938", "GSM3200939", "GSM3200940", "GSM3200941", "GSM3200942", "GSM3200943", "GSM3200944", "GSM3200945", "GSM3200946", "GSM3200947", "GSM3200948", "GSM3200949", "GSM3200950", "GSM3200951", "GSM3200952", "GSM3200953", "GSM3200954", "GSM3200955", "GSM3200956", "GSM3200957", "GSM3200958", "GSM3200959", "GSM3200960", "GSM3200961", "GSM3200962", "GSM3200963", "GSM3200964", "GSM3200965", "GSM3200966", "GSM3200967", "GSM3200968", "GSM3200969", "GSM3200970", "GSM3200971", "GSM3200972", "GSM3200973", "GSM3200974", "GSM3200975", "GSM3200976", "GSM3200977", "GSM3200978", "GSM3200979", "GSM3200980", "GSM3200981", "GSM3200982", "GSM3200983", "GSM3200984", "GSM3200985", "GSM3200986", "GSM3200987", "GSM3200988", "GSM3200989", "GSM3200990", "GSM3200991", "GSM3200992", "GSM3200993", "GSM3200994", "GSM3200995", "GSM3200996", "GSM3200997", "GSM3200998", "GSM3200999", "GSM3201000", "GSM3201001", "GSM3201002", "GSM3201003", "GSM3201004", "GSM3201005", "GSM3201006", "GSM3201007", "GSM3201008", "GSM3201009", "GSM3201010", "GSM3201011", "GSM3201012", "GSM3201013", "GSM3201014", "GSM3201015", "GSM3201016", "GSM3201017", "GSM3201018", "GSM3201019", "GSM3201020", "GSM3201021", "GSM3201022", "GSM3201023", "GSM3201024", "GSM3201025", "GSM3201026", "GSM3201027", "GSM3201028", "GSM3201029", "GSM3201030", "GSM3201031", "GSM3201032", "GSM3201033", "GSM3201034", "GSM3201035", "GSM3201036", "GSM3201037", "GSM3201038", "GSM3201039", "GSM3201040", "GSM3201041", "GSM3201042", "GSM3201043", "GSM3201044", "GSM3201045", "GSM3201046", "GSM3201047", "GSM3201048", "GSM3201049", "GSM3201050", "GSM3201051", "GSM3201052", "GSM3201053", "GSM3201054", "GSM3201055", "GSM3201056", "GSM3201057", "GSM3201058", "GSM3201059", "GSM3201060", "GSM3201061", "GSM3201062", "GSM3201063", "GSM3201064", "GSM3201065", "GSM3201066", "GSM3201067", "GSM3201068", "GSM3201069", "GSM3201070", "GSM3201071", "GSM3201072", "GSM3201073", "GSM3201074", "GSM3201075", "GSM3201076", "GSM3201077", "GSM3201078", "GSM3201079", "GSM3201080", "GSM3201081", "GSM3201082", "GSM3201083", "GSM3201084", "GSM3201085", "GSM3201086", "GSM3201087", "GSM3201088", "GSM3201089", "GSM3201090", "GSM3201091", "GSM3201092", "GSM3201093", "GSM3201094", "GSM3201095", "GSM3201096", "GSM3201097", "GSM3201098", "GSM3201099", "GSM3201100", "GSM3201101", "GSM3201102", "GSM3201103", "GSM3201104", "GSM3201105", "GSM3201106", "GSM3201107", "GSM3201108", "GSM3201109", "GSM3201110", "GSM3201111", "GSM3201112", "GSM3201113", "GSM3201114", "GSM3201115", "GSM3201116", "GSM3201117", "GSM3201118", "GSM3201119", "GSM3201120", "GSM3201121", "GSM3201122", "GSM3201123", "GSM3201124", "GSM3201125", "GSM3201126", "GSM3201127", "GSM3201128", "GSM3201129", "GSM3201130", "GSM3201131", "GSM3201132", "GSM3201133", "GSM3201134", "GSM3201135", "GSM3201136", "GSM3201137", "GSM3201138", "GSM3201139", "GSM3201140", "GSM3201141", "GSM3201142", "GSM3201143", "GSM3201144", "GSM3201145", "GSM3201146", "GSM3201147", "GSM3201148", "GSM3201149", "GSM3201150", "GSM3201151", "GSM3201152", "GSM3201153", "GSM3201154", "GSM3201155", "GSM3201156", "GSM3201157", "GSM3201158", "GSM3201159", "GSM3201160", "GSM3201161", "GSM3201162", "GSM3201163", "GSM3201164", "GSM3201165", "GSM3201166", "GSM3201167", "GSM3201168", "GSM3201169", "GSM3201170", "GSM3201171", "GSM3201172", "GSM3201173", "GSM3201174", "GSM3201175", "GSM3201176", "GSM3201177", "GSM3201178", "GSM3201179", "GSM3201180", "GSM3201181", "GSM3201182", "GSM3201183", "GSM3201184", "GSM3201185", "GSM3201186", "GSM3201187", "GSM3201188", "GSM3201189", "GSM3201190", "GSM3201191", "GSM3201192", "GSM3201193", "GSM3201194", "GSM3201195", "GSM3201196", "GSM3201197", "GSM3201198", "GSM3201199", "GSM3201200", "GSM3201201", "GSM3201202", "GSM3201203", "GSM3201204", "GSM3201205", "GSM3201206", "GSM3201207", "GSM3201208", "GSM3201209", "GSM3201210", "GSM3201211", "GSM3201212", "GSM3201213", "GSM3201214", "GSM3201215", "GSM3201216", "GSM3201217", "GSM3201218", "GSM3201219", "GSM3201220", "GSM3201221", "GSM3201222", "GSM3201223", "GSM3201224", "GSM3201225", "GSM3201226", "GSM3201227", "GSM3201228", "GSM3201229", "GSM3201230", "GSM3201231", "GSM3201232", "GSM3201233", "GSM3201234", "GSM3201235", "GSM3201236", "GSM3201237", "GSM3201238", "GSM3201239", "GSM3201240", "GSM3201241", "GSM3201242", "GSM3201243", "GSM3201244", "GSM3201245", "GSM3201246", "GSM3201247", "GSM3201248", "GSM3201249", "GSM3201250", "GSM3201251", "GSM3201252", "GSM3201253", "GSM3201254", "GSM3201255", "GSM3201256", "GSM3201257", "GSM3201258", "GSM3201259", "GSM3201260", "GSM3201261", "GSM3201262", "GSM3201263", "GSM3201264", "GSM3201265", "GSM3201266", "GSM3201267", "GSM3201268", "GSM3201269", "GSM3201270", "GSM3201271", "GSM3201272", "GSM3201273", "GSM3201274", "GSM3201275", "GSM3201276", "GSM3201277", "GSM3201278", "GSM3201279", "GSM3201280", "GSM3201281", "GSM3201282", "GSM3201283", "GSM3201284", "GSM3201285", "GSM3201286", "GSM3201287", "GSM3201288", "GSM3201289", "GSM3201290", "GSM3201291", "GSM3201292", "GSM3201293", "GSM3201294", "GSM3201295", "GSM3201296", "GSM3201297", "GSM3201298", "GSM3201299", "GSM3201300", "GSM3201301", "GSM3201302", "GSM3201303", "GSM3201304", "GSM3201305", "GSM3201306", "GSM3201307", "GSM3201308", "GSM3201309", "GSM3201310", "GSM3201311", "GSM3201312", "GSM3201313", "GSM3201314", "GSM3201315", "GSM3201316", "GSM3201317", "GSM3201318", "GSM3201319", "GSM3201320", "GSM3201321", "GSM3201322", "GSM3201323", "GSM3201324", "GSM3201325", "GSM3201326", "GSM3201327", "GSM3201328", "GSM3201329", "GSM3201330", "GSM3201331", "GSM3201332", "GSM3201333", "GSM3201334", "GSM3201335", "GSM3201336", "GSM3201337", "GSM3201338", "GSM3201339", "GSM3201340", "GSM3201341", "GSM3201342", "GSM3201343", "GSM3201344", "GSM3201345", "GSM3201346", "GSM3201347", "GSM3201348", "GSM3201349", "GSM3201350", "GSM3201351", "GSM3201352", "GSM3201353", "GSM3201354", "GSM3201355", "GSM3201356", "GSM3201357", "GSM3201358", "GSM3201359", "GSM3201360", "GSM3201361", "GSM3201362", "GSM3201363", "GSM3201364", "GSM3201365", "GSM3201366", "GSM3201367", "GSM3201368", "GSM3201369", "GSM3201370", "GSM3201371", "GSM3201372", "GSM3201373", "GSM3201374", "GSM3201375", "GSM3201376", "GSM3201377", "GSM3201378", "GSM3201379", "GSM3201380", "GSM3201381", "GSM3201382", "GSM3201383", "GSM3201384", "GSM3201385", "GSM3201386", "GSM3201387", "GSM3201388", "GSM3201389", "GSM3201390", "GSM3201391", "GSM3201392", "GSM3201393", "GSM3201394", "GSM3201395", "GSM3201396", "GSM3201397", "GSM3201398", "GSM3201399", "GSM3201400", "GSM3201401", "GSM3201402", "GSM3201403", "GSM3201404", "GSM3201405", "GSM3201406", "GSM3201407", "GSM3201408", "GSM3201409", "GSM3201410", "GSM3201411", "GSM3201412", "GSM3201413", "GSM3201414", "GSM3201415", "GSM3201416", "GSM3201417", "GSM3201418", "GSM3201419", "GSM3201420", "GSM3201421", "GSM3201422", "GSM3201423", "GSM3201424", "GSM3201425", "GSM3201426", "GSM3201427", "GSM3201428", "GSM3201429", "GSM3201430", "GSM3201431", "GSM3201432", "GSM3201433", "GSM3201434", "GSM3201435", "GSM3201436", "GSM3201437", "GSM3201438", "GSM3201439", "GSM3201440", "GSM3201441", "GSM3201442", "GSM3201443", "GSM3201444", "GSM3201445", "GSM3201446", "GSM3201447", "GSM3201448", "GSM3201449", "GSM3201450", "GSM3201451", "GSM3201452", "GSM3201453", "GSM3201454", "GSM3201455", "GSM3201456", "GSM3201457", "GSM3201458", "GSM3201459", "GSM3201460", "GSM3201461", "GSM3201462", "GSM3201463", "GSM3201464", "GSM3201465", "GSM3201466", "GSM3201467", "GSM3201468", "GSM3201469", "GSM3201470", "GSM3201471", "GSM3201472", "GSM3201473", "GSM3201474", "GSM3201475", "GSM3201476", "GSM3201477", "GSM3201478", "GSM3201479", "GSM3201480", "GSM3201481", "GSM3201482", "GSM3201483", "GSM3201484", "GSM3201485", "GSM3201486", "GSM3201487", "GSM3201488", "GSM3201489", "GSM3201490", "GSM3201491", "GSM3201492", "GSM3201493", "GSM3201494", "GSM3201495", "GSM3201496", "GSM3201497", "GSM3201498", 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"GSM3201570", "GSM3201571", "GSM3201572", "GSM3201573", "GSM3201574", "GSM3201575", "GSM3201576", "GSM3201577", "GSM3201578", "GSM3201579", "GSM3201580", "GSM3201581", "GSM3201582", "GSM3201583", "GSM3201584", "GSM3201585", "GSM3201586", "GSM3201587", "GSM3201588", "GSM3201589", "GSM3201590", "GSM3201591", "GSM3201592", "GSM3201593", "GSM3201594", "GSM3201595", "GSM3201596", "GSM3201597", "GSM3201598", "GSM3201599", "GSM3201600", "GSM3201601", "GSM3201602", "GSM3201603", "GSM3201604", "GSM3201605", "GSM3201606", "GSM3201607", "GSM3201608", "GSM3201609", "GSM3201610", "GSM3201611", "GSM3201612", "GSM3201613", "GSM3201614", "GSM3201615", "GSM3201616", "GSM3201617", "GSM3201618", "GSM3201619", "GSM3201620", "GSM3201621", "GSM3201622", "GSM3201623", "GSM3201624", "GSM3201625", "GSM3201626", "GSM3201627", "GSM3201628", "GSM3201629", "GSM3201630", "GSM3201631", "GSM3201632", "GSM3201633", "GSM3201634", "GSM3201635", "GSM3201636", "GSM3201637", "GSM3201638", "GSM3201639", "GSM3201640", 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"GSM3201783", "GSM3201784", "GSM3201785", "GSM3201786", "GSM3201787", "GSM3201788", "GSM3201789", "GSM3201790", "GSM3201791", "GSM3201792", "GSM3201793", "GSM3201794", "GSM3201795", "GSM3201796", "GSM3201797", "GSM3201798", "GSM3201799", "GSM3201800", "GSM3201801", "GSM3201802", "GSM3201803", "GSM3201804", "GSM3201805", "GSM3201806", "GSM3201807", "GSM3201808", "GSM3201809", "GSM3201810", "GSM3201811", "GSM3201812", "GSM3201813", "GSM3201814", "GSM3201815", "GSM3201816", "GSM3201817", "GSM3201818", "GSM3201819", "GSM3201820", "GSM3201821", "GSM3201822", "GSM3201823", "GSM3201824", "GSM3201825", "GSM3201826", "GSM3201827", "GSM3201828", "GSM3201829", "GSM3201830", "GSM3201831", "GSM3201832", "GSM3201833", "GSM3201834", "GSM3201835", "GSM3201836", "GSM3201837", "GSM3201838", "GSM3201839", "GSM3201840", "GSM3201841", "GSM3201842", "GSM3201843", "GSM3201844", "GSM3201845", "GSM3201846", "GSM3201847", "GSM3201848", "GSM3201849", "GSM3201850", "GSM3201851", "GSM3201852", "GSM3201853", "GSM3201854", "GSM3201855", "GSM3201856", "GSM3201857", "GSM3201858", "GSM3201859", "GSM3201860", "GSM3201861", "GSM3201862", "GSM3201863", "GSM3201864", "GSM3201865", "GSM3201866", "GSM3201867", "GSM3201868", "GSM3201869", "GSM3201870", "GSM3201871", "GSM3201872", "GSM3201873", "GSM3201874", "GSM3201875", "GSM3201876", "GSM3201877", "GSM3201878", "GSM3201879", "GSM3201880", "GSM3201881", "GSM3201882", "GSM3201883", "GSM3201884", "GSM3201885", "GSM3201886", "GSM3201887", "GSM3201888", "GSM3201889", "GSM3201890", "GSM3201891", "GSM3201892", "GSM3201893", "GSM3201894", "GSM3201895", "GSM3201896", "GSM3201897", "GSM3201898", "GSM3201899", "GSM3201900", "GSM3201901", "GSM3201902", "GSM3201903", "GSM3201904", "GSM3201905", "GSM3201906", "GSM3201907", "GSM3201908", "GSM3201909", "GSM3201910", "GSM3201911", "GSM3201912", "GSM3201913", "GSM3201914", "GSM3201915", "GSM3201916", "GSM3201917", "GSM3201918", "GSM3201919", "GSM3201920", "GSM3201921", "GSM3201922", "GSM3201923", "GSM3201924", "GSM3201925", "GSM3201926", "GSM3201927", "GSM3201928", "GSM3201929", "GSM3201930", "GSM3201931", "GSM3201932", "GSM3201933", "GSM3201934", "GSM3201935", "GSM3201936", "GSM3201937", "GSM3201938", "GSM3201939", "GSM3201940", "GSM3201941", "GSM3201942", "GSM3201943", "GSM3201944", "GSM3201945", "GSM3201946", "GSM3201947", "GSM3201948", "GSM3201949", "GSM3201950", "GSM3201951", "GSM3201952", "GSM3201953", "GSM3201954", "GSM3201955", "GSM3201956", "GSM3201957", "GSM3201958", "GSM3201959", "GSM3201960", "GSM3201961", "GSM3201962", "GSM3201963", "GSM3201964", "GSM3201965", "GSM3201966", "GSM3201967", "GSM3201968", "GSM3201969", "GSM3201970", "GSM3201971", "GSM3201972", "GSM3201973", "GSM3201974", "GSM3201975", "GSM3201976", "GSM3201977", "GSM3201978", "GSM3201979", "GSM3201980", "GSM3201981", "GSM3201982", "GSM3201983", "GSM3201984", "GSM3201985", "GSM3201986", "GSM3201987", "GSM3201988", "GSM3201989", "GSM3201990", "GSM3201991", "GSM3201992", "GSM3201993", "GSM3201994", "GSM3201995", "GSM3201996", "GSM3201997", "GSM3201998", "GSM3201999", "GSM3202000", "GSM3202001", "GSM3202002", "GSM3202003", "GSM3202004", "GSM3202005", "GSM3202006", "GSM3202007", "GSM3202008", "GSM3202009", "GSM3202010", "GSM3202011", "GSM3202012", "GSM3202013", "GSM3202014", "GSM3202015", "GSM3202016", "GSM3202017", "GSM3202018", "GSM3202019", "GSM3202020", "GSM3202021", "GSM3202022", "GSM3202023", "GSM3202024", "GSM3202025", "GSM3202026", "GSM3202027", "GSM3202028", "GSM3202029", "GSM3202030", "GSM3202031", "GSM3202032", "GSM3202033", "GSM3202034", "GSM3202035", "GSM3202036", "GSM3202037", "GSM3202038", "GSM3202039", "GSM3202040", "GSM3202041", "GSM3202042", "GSM3202043", "GSM3202044", "GSM3202045", "GSM3202046", "GSM3202047", "GSM3202048", "GSM3202049", "GSM3202050", "GSM3202051", "GSM3202052", "GSM3202053", "GSM3202054", "GSM3202055", "GSM3202056", "GSM3202057", "GSM3202058", "GSM3202059", "GSM3202060", "GSM3202061", "GSM3202062", "GSM3202063", "GSM3202064", "GSM3202065", "GSM3202066", "GSM3202067", "GSM3202068", "GSM3202069", "GSM3202070", "GSM3202071", "GSM3202072", "GSM3202073", "GSM3202074", "GSM3202075", "GSM3202076", "GSM3202077", "GSM3202078", "GSM3202079", "GSM3202080", "GSM3202081", "GSM3202082", "GSM3202083", "GSM3202084", "GSM3202085", "GSM3202086", "GSM3202087", "GSM3202088", "GSM3202089", "GSM3202090", "GSM3202091", "GSM3202092", "GSM3202093", "GSM3202094", "GSM3202095", "GSM3202096", "GSM3202097", "GSM3202098", "GSM3202099", "GSM3202100", "GSM3202101", "GSM3202102", "GSM3202103", "GSM3202104", "GSM3202105", "GSM3202106", "GSM3202107", "GSM3202108", "GSM3202109", "GSM3202110", "GSM3202111", "GSM3202112", "GSM3202113", "GSM3202114", "GSM3202115", "GSM3202116", "GSM3202117", "GSM3202118", "GSM3202119", "GSM3202120", "GSM3202121", "GSM3202122", "GSM3202123", "GSM3202124", "GSM3202125", "GSM3202126", "GSM3202127", "GSM3202128", "GSM3202129", "GSM3202130", "GSM3202131", "GSM3202132", "GSM3202133", "GSM3202134", "GSM3202135", "GSM3202136", "GSM3202137", "GSM3202138", "GSM3202139", "GSM3202140", "GSM3202141", "GSM3202142", "GSM3202143", "GSM3202144", "GSM3202145", "GSM3202146", "GSM3202147", "GSM3202148", "GSM3202149", "GSM3202150", "GSM3202151", "GSM3202152", "GSM3202153", "GSM3202154", "GSM3202155", "GSM3202156", "GSM3202157", "GSM3202158", "GSM3202159", "GSM3202160", "GSM3202161", "GSM3202162", "GSM3202163", "GSM3202164", "GSM3202165", "GSM3202166", "GSM3202167", "GSM3202168", "GSM3202169", "GSM3202170", "GSM3202171", "GSM3202172", "GSM3202173", "GSM3202174", "GSM3202175", "GSM3202176", "GSM3202177", "GSM3202178", "GSM3202179", "GSM3202180", "GSM3202181", "GSM3202182", "GSM3202183", "GSM3202184", "GSM3202185", "GSM3202186", "GSM3202187", "GSM3202188", "GSM3202189", "GSM3202190", "GSM3202191", "GSM3202192", "GSM3202193", "GSM3202194", "GSM3202195", "GSM3202196", "GSM3202197", "GSM3202198", "GSM3202199", "GSM3202200", "GSM3202201", "GSM3202202", "GSM3202203", "GSM3202204", "GSM3202205", "GSM3202206", "GSM3202207", "GSM3202208", "GSM3202209", "GSM3202210", "GSM3202211", "GSM3202212", "GSM3202213", "GSM3202214", "GSM3202215", "GSM3202216", "GSM3202217", "GSM3202218", "GSM3202219", "GSM3202220", "GSM3202221", "GSM3202222", "GSM3202223", "GSM3202224", "GSM3202225", "GSM3202226", "GSM3202227", "GSM3202228", "GSM3202229", "GSM3202230", "GSM3202231", "GSM3202232", "GSM3202233", "GSM3202234", "GSM3202235", "GSM3202236", "GSM3202237", "GSM3202238", "GSM3202239", "GSM3202240", "GSM3202241", "GSM3202242", "GSM3202243", "GSM3202244", "GSM3202245", "GSM3202246", "GSM3202247", "GSM3202248", "GSM3202249", "GSM3202250", "GSM3202251", "GSM3202252", "GSM3202253", "GSM3202254", "GSM3202255", "GSM3202256", "GSM3202257", "GSM3202258", "GSM3202259", "GSM3202260", "GSM3202261", "GSM3202262", "GSM3202263", "GSM3202264", "GSM3202265", "GSM3202266", "GSM3202267", "GSM3202268", "GSM3202269", "GSM3202270", "GSM3202271", "GSM3202272", "GSM3202273", "GSM3202274", "GSM3202275", "GSM3202276", "GSM3202277", "GSM3202278", "GSM3202279", "GSM3202280", "GSM3202281", "GSM3202282", "GSM3202283", "GSM3202284", "GSM3202285", "GSM3202286", "GSM3202287", "GSM3202288", "GSM3202289", "GSM3202290", "GSM3202291", "GSM3202292", "GSM3202293", "GSM3202294", "GSM3202295", "GSM3202296", "GSM3202297", "GSM3202298", "GSM3202299", "GSM3202300", "GSM3202301", "GSM3202302", "GSM3202303", "GSM3202304", "GSM3202305", "GSM3202306", "GSM3202307", "GSM3202308", "GSM3202309", "GSM3202310", "GSM3202311", "GSM3202312", "GSM3202313", "GSM3202314", "GSM3202315", "GSM3202316", "GSM3202317", "GSM3202318", "GSM3202319", "GSM3202320", "GSM3202321", "GSM3202322", "GSM3202323", "GSM3202324", "GSM3202325", "GSM3202326", "GSM3202327", "GSM3202328", "GSM3202329", "GSM3202330", "GSM3202331", "GSM3202332", "GSM3202333", "GSM3202334", "GSM3202335", "GSM3202336", "GSM3202337", "GSM3202338", "GSM3202339", "GSM3202340", "GSM3202341", "GSM3202342", "GSM3202343", "GSM3202344", "GSM3202345", "GSM3202346", "GSM3202347", "GSM3202348", "GSM3202349", "GSM3202350", "GSM3202351", "GSM3202352", "GSM3202353", "GSM3202354", "GSM3202355", "GSM3202356", "GSM3202357", "GSM3202358", "GSM3202359", "GSM3202360", "GSM3202361", "GSM3202362", "GSM3202363", "GSM3202364", "GSM3202365", "GSM3202366", "GSM3202367", "GSM3202368", "GSM3202369", "GSM3202370", "GSM3202371", "GSM3202372", "GSM3202373", "GSM3202374", "GSM3202375", "GSM3202376", "GSM3202377", "GSM3202378", "GSM3202379", "GSM3202380", "GSM3202381", "GSM3202382", "GSM3202383", "GSM3202384", "GSM3202385", "GSM3202386", "GSM3202387", "GSM3202388", "GSM3202389", "GSM3202390", "GSM3202391", "GSM3202392", "GSM3202393", "GSM3202394", "GSM3202395", "GSM3202396", "GSM3202397", "GSM3202398", "GSM3202399", "GSM3202400", "GSM3202401", "GSM3202402", "GSM3202403", "GSM3202404", "GSM3202405", "GSM3202406", "GSM3202407", "GSM3202408", "GSM3202409", "GSM3202410", "GSM3202411", "GSM3202412", "GSM3202413", "GSM3202414", "GSM3202415", "GSM3202416", "GSM3202417", "GSM3202418", "GSM3202419", "GSM3202420", "GSM3202421", "GSM3202422", "GSM3202423", "GSM3202424", "GSM3202425", "GSM3202426", "GSM3202427", "GSM3202428", "GSM3202429", "GSM3202430", "GSM3202431", "GSM3202432", "GSM3202433", "GSM3202434", "GSM3202435", "GSM3202436", "GSM3202437", "GSM3202438", "GSM3202439", "GSM3202440", "GSM3202441", "GSM3202442", "GSM3202443", "GSM3202444", "GSM3202445", "GSM3202446", "GSM3202447", "GSM3202448", "GSM3202449", "GSM3202450", "GSM3202451", "GSM3202452", "GSM3202453", "GSM3202454", "GSM3202455", "GSM3202456", "GSM3202457", "GSM3202458", "GSM3202459", "GSM3202460", "GSM3202461", "GSM3202462", "GSM3202463", "GSM3202464", "GSM3202465", "GSM3202466", "GSM3202467", "GSM3202468", "GSM3202469", "GSM3202470", "GSM3202471", "GSM3202472", "GSM3202473", "GSM3202474", "GSM3202475", "GSM3202476", "GSM3202477", "GSM3202478", "GSM3202479", "GSM3202480", "GSM3202481", "GSM3202482", "GSM3202483", "GSM3202484", "GSM3202485", "GSM3202486", "GSM3202487", "GSM3202488", "GSM3202489", "GSM3202490", "GSM3202491", "GSM3202492", "GSM3202493", "GSM3202494", "GSM3202495", "GSM3202496", "GSM3202497", "GSM3202498", "GSM3202499", "GSM3202500", "GSM3202501", "GSM3202502", "GSM3202503", "GSM3202504", "GSM3202505", "GSM3202506", "GSM3202507", "GSM3202508", "GSM3202509", "GSM3202510", "GSM3202511", "GSM3202512", "GSM3202513", "GSM3202514", "GSM3202515", "GSM3202516", "GSM3202517", "GSM3202518", "GSM3202519", "GSM3202520", "GSM3202521", "GSM3202522", "GSM3202523", "GSM3202524", "GSM3202525", "GSM3202526", "GSM3202527", "GSM3202528", "GSM3202529", "GSM3202530", "GSM3202531", "GSM3202532", "GSM3202533", "GSM3202534", "GSM3202535", "GSM3202536", "GSM3202537", "GSM3202538", "GSM3202539", "GSM3202540", "GSM3202541", "GSM3202542", "GSM3202543", "GSM3202544", "GSM3202545", "GSM3202546", "GSM3202547", "GSM3202548", "GSM3202549", "GSM3202550", "GSM3202551", "GSM3202552", "GSM3202553", "GSM3202554", "GSM3202555", "GSM3202556", "GSM3202557", "GSM3202558", "GSM3202559", "GSM3202560", "GSM3202561", "GSM3202562", "GSM3202563", "GSM3202564", "GSM3202565", "GSM3202566", "GSM3202567", "GSM3202568", "GSM3202569", "GSM3202570", "GSM3202571", "GSM3202572", "GSM3202573", "GSM3202574", "GSM3202575", "GSM3202576", "GSM3202577", "GSM3202578", "GSM3202579", "GSM3202580", "GSM3202581", "GSM3202582", "GSM3202583", "GSM3202584", "GSM3202585", "GSM3202586", "GSM3202587", "GSM3202588", "GSM3202589", "GSM3202590", "GSM3202591", "GSM3202592", "GSM3202593", "GSM3202594", "GSM3202595", "GSM3202596", "GSM3202597", "GSM3202598", "GSM3202599", "GSM3202600", "GSM3202601", "GSM3202602", "GSM3202603", "GSM3202604", "GSM3202605", "GSM3202606", "GSM3202607", "GSM3202608", "GSM3202609", "GSM3202610", "GSM3202611", "GSM3202612", "GSM3202613", "GSM3202614", "GSM3202615", "GSM3202616", "GSM3202617", "GSM3202618", "GSM3202619", "GSM3202620", "GSM3202621", "GSM3202622", "GSM3202623", "GSM3202624", "GSM3202625", "GSM3202626", "GSM3202627", "GSM3202628", "GSM3202629", "GSM3202630", "GSM3202631", "GSM3202632", "GSM3202633", "GSM3202634", "GSM3202635", "GSM3202636", "GSM3202637", "GSM3202638", "GSM3202639", "GSM3202640", "GSM3202641", "GSM3202642", "GSM3202643", "GSM3202644", "GSM3202645", "GSM3202646", "GSM3202647", "GSM3202648", "GSM3202649", "GSM3202650", "GSM3202651", "GSM3202652", "GSM3202653", "GSM3202654", "GSM3202655", "GSM3202656", "GSM3202657", "GSM3202658", "GSM3202659", "GSM3202660", "GSM3202661", "GSM3202662", "GSM3202663", "GSM3202664", "GSM3202665", "GSM3202666", "GSM3202667", "GSM3202668", "GSM3202669", "GSM3202670", "GSM3202671", "GSM3202672", "GSM3202673", "GSM3202674", "GSM3202675", "GSM3202676", "GSM3202677", "GSM3202678", "GSM3202679", "GSM3202680", "GSM3202681", "GSM3202682", "GSM3202683", "GSM3202684", "GSM3202685", "GSM3202686", "GSM3202687", "GSM3202688", "GSM3202689", "GSM3202690", "GSM3202691", "GSM3202692", "GSM3202693", "GSM3202694", "GSM3202695", "GSM3202696", "GSM3202697", "GSM3202698", "GSM3202699", "GSM3202700", "GSM3202701", "GSM3202702", "GSM3202703", "GSM3202704", "GSM3202705", "GSM3202706", "GSM3202707", "GSM3202708", "GSM3202709", "GSM3202710", "GSM3202711", "GSM3202712", "GSM3202713", "GSM3202714", "GSM3202715", "GSM3202716", "GSM3202717", "GSM3202718", "GSM3202719", "GSM3202720", "GSM3202721", "GSM3202722", "GSM3202723", "GSM3202724", "GSM3202725", "GSM3202726", "GSM3202727", "GSM3202728", "GSM3202729", "GSM3202730", "GSM3202731", "GSM3202732", "GSM3202733", "GSM3202734", "GSM3202735", "GSM3202736", "GSM3202737", "GSM3202738", "GSM3202739", "GSM3202740", "GSM3202741", "GSM3202742", "GSM3202743", "GSM3202744", "GSM3202745", "GSM3202746", "GSM3202747", "GSM3202748", "GSM3202749", "GSM3202750", "GSM3202751", "GSM3202752", "GSM3202753", "GSM3202754", "GSM3202755", "GSM3202756", "GSM3202757", "GSM3202758", "GSM3202759", "GSM3202760", "GSM3202761", "GSM3202762", "GSM3202763", "GSM3202764", "GSM3202765", "GSM3202766", "GSM3202767", "GSM3202768", "GSM3202769", "GSM3202770", "GSM3202771", "GSM3202772", "GSM3202773", "GSM3202774", "GSM3202775", "GSM3202776", "GSM3202777", "GSM3202778", "GSM3202779", "GSM3202780", "GSM3202781", "GSM3202782", "GSM3202783", "GSM3202784", "GSM3202785", "GSM3202786", "GSM3202787", "GSM3202788", "GSM3202789", "GSM3202790", "GSM3202791", "GSM3202792", "GSM3202793", "GSM3202794", "GSM3202795", "GSM3202796", "GSM3202797", "GSM3202798", "GSM3202799", "GSM3202800", "GSM3202801", "GSM3202802", "GSM3202803", "GSM3202804", "GSM3202805", "GSM3202806", "GSM3202807", "GSM3202808", "GSM3202809", "GSM3202810", "GSM3202811", "GSM3202812", "GSM3202813", "GSM3202814", "GSM3202815", "GSM3202816", "GSM3202817", "GSM3202818", "GSM3202819", "GSM3202820", "GSM3202821", "GSM3202822", "GSM3202823", "GSM3202824", "GSM3202825", "GSM3202826", "GSM3202827", "GSM3202828", "GSM3202829", "GSM3202830", "GSM3202831", "GSM3202832", "GSM3202833", "GSM3202834", "GSM3202835", "GSM3202836", "GSM3202837", "GSM3202838", "GSM3202839", "GSM3202840", "GSM3202841", "GSM3202842", "GSM3202843", "GSM3202844", "GSM3202845", "GSM3202846", "GSM3202847", "GSM3202848", "GSM3202849", "GSM3202850", "GSM3202851", "GSM3202852", "GSM3202853", "GSM3202854", "GSM3202855", "GSM3202856", "GSM3202857", "GSM3202858", "GSM3202859", "GSM3202860", "GSM3202861", "GSM3202862", "GSM3202863", "GSM3202864", "GSM3202865", "GSM3202866", "GSM3202867", "GSM3202868", "GSM3202869", "GSM3202870", "GSM3202871", "GSM3202872", "GSM3202873", "GSM3202874", "GSM3202875", "GSM3202876", "GSM3202877", "GSM3202878", "GSM3202879", "GSM3202880", "GSM3202881", "GSM3202882", "GSM3202883", "GSM3202884", "GSM3202885", "GSM3202886", "GSM3202887", "GSM3202888", "GSM3202889", "GSM3202890", "GSM3202891", "GSM3202892", "GSM3202893", "GSM3202894", "GSM3202895", "GSM3202896", "GSM3202897", "GSM3202898", "GSM3202899", "GSM3202900", "GSM3202901", "GSM3202902", "GSM3202903", "GSM3202904", "GSM3202905", "GSM3202906", "GSM3202907", "GSM3202908", "GSM3202909", "GSM3202910", "GSM3202911", "GSM3202912", "GSM3202913", "GSM3202914", "GSM3202915", "GSM3202916", "GSM3202917", "GSM3202918", "GSM3202919", "GSM3202920", "GSM3202921", "GSM3202922", "GSM3202923", "GSM3202924", "GSM3202925", "GSM3202926", "GSM3202927", "GSM3202928", "GSM3202929", "GSM3202930", "GSM3202931", "GSM3202932", "GSM3202933", "GSM3202934", "GSM3202935", "GSM3202936", "GSM3202937", "GSM3202938", "GSM3202939", "GSM3202940", "GSM3202941", "GSM3202942", "GSM3202943", "GSM3202944", "GSM3202945", "GSM3202946", "GSM3202947", "GSM3202948", "GSM3202949", "GSM3202950", "GSM3202951", "GSM3202952", "GSM3202953", "GSM3202954", "GSM3202955", "GSM3202956", "GSM3202957", "GSM3202958", "GSM3202959", "GSM3202960", "GSM3202961", "GSM3202962", "GSM3202963", "GSM3202964", "GSM3202965", "GSM3202966", "GSM3202967", "GSM3202968", "GSM3202969", "GSM3202970", "GSM3202971", "GSM3202972", "GSM3202973", "GSM3202974", "GSM3202975", "GSM3202976", "GSM3202977", "GSM3202978", "GSM3202979", "GSM3202980", "GSM3202981", "GSM3202982", "GSM3202983", "GSM3202984", "GSM3202985", "GSM3202986", "GSM3202987", "GSM3202988", "GSM3202989", "GSM3202990", "GSM3202991", "GSM3202992", "GSM3202993", "GSM3202994", "GSM3202995", "GSM3202996", "GSM3202997", "GSM3202998", "GSM3202999", "GSM3203000", "GSM3203001", "GSM3203002", "GSM3203003", "GSM3203004", "GSM3203005", "GSM3203006", "GSM3203007", "GSM3203008", "GSM3203009", "GSM3203010", "GSM3203011", "GSM3203012", "GSM3203013", "GSM3203014", "GSM3203015", "GSM3203016", "GSM3203017", "GSM3203018", "GSM3203019", "GSM3203020", "GSM3203021", "GSM3203022", "GSM3203023", "GSM3203024", "GSM3203025", "GSM3203026", "GSM3203027", "GSM3203028", "GSM3203029", "GSM3203030", "GSM3203031", "GSM3203032", "GSM3203033", "GSM3203034", "GSM3203035", "GSM3203036", "GSM3203037", "GSM3203038", "GSM3203039", "GSM3203040", "GSM3203041", "GSM3203042", "GSM3203043", "GSM3203044", "GSM3203045", "GSM3203046", "GSM3203047", "GSM3203048", "GSM3203049", "GSM3203050", "GSM3203051", "GSM3203052", "GSM3203053", "GSM3203054", "GSM3203055", "GSM3203056", "GSM3203057", "GSM3203058", "GSM3203059", "GSM3203060", "GSM3203061", "GSM3203062", "GSM3203063", "GSM3203064", "GSM3203065", "GSM3203066", "GSM3203067", "GSM3203068", "GSM3203069", "GSM3203070", "GSM3203071", "GSM3203072", "GSM3203073", "GSM3203074", "GSM3203075", "GSM3203076", "GSM3203077", "GSM3203078", "GSM3203079", "GSM3203080", "GSM3203081", "GSM3203082", "GSM3203083", "GSM3203084", "GSM3203085", "GSM3203086", "GSM3203087", "GSM3203088", "GSM3203089", "GSM3203090", "GSM3203091", "GSM3203092", "GSM3203093", "GSM3203094", "GSM3203095", "GSM3203096", "GSM3203097", "GSM3203098", "GSM3203099", "GSM3203100", "GSM3203101", "GSM3203102", "GSM3203103", "GSM3203104", "GSM3203105", "GSM3203106", "GSM3203107", "GSM3203108", "GSM3203109", "GSM3203110", "GSM3203111", "GSM3203112", "GSM3203113", "GSM3203114", "GSM3203115", "GSM3203116", "GSM3203117", "GSM3203118", "GSM3203119", "GSM3203120", "GSM3203121", "GSM3203122", "GSM3203123", "GSM3203124", "GSM3203125", "GSM3203126", "GSM3203127", "GSM3203128", "GSM3203129", "GSM3203130", "GSM3203131", "GSM3203132", "GSM3203133", "GSM3203134", "GSM3203135", "GSM3203136", "GSM3203137", "GSM3203138", "GSM3203139", "GSM3203140", "GSM3203141", "GSM3203142", "GSM3203143", "GSM3203144", "GSM3203145", "GSM3203146", "GSM3203147", "GSM3203148", "GSM3203149", "GSM3203150", "GSM3203151", "GSM3203152", "GSM3203153", "GSM3203154", "GSM3203155", "GSM3203156", "GSM3203157", "GSM3203158", "GSM3203159", "GSM3203160", "GSM3203161", "GSM3203162", "GSM3203163", "GSM3203164", "GSM3203165", "GSM3203166", "GSM3203167", "GSM3203168", "GSM3203169", "GSM3203170", "GSM3203171", "GSM3203172", "GSM3203173", "GSM3203174", "GSM3203175", "GSM3203176", "GSM3203177", "GSM3203178", "GSM3203179", "GSM3203180", "GSM3203181", "GSM3203182", "GSM3203183", "GSM3203184", "GSM3203185", "GSM3203186", "GSM3203187", "GSM3203188", "GSM3203189", "GSM3203190", "GSM3203191", "GSM3203192", "GSM3203193", "GSM3203194", "GSM3203195", "GSM3203196", "GSM3203197", "GSM3203198", "GSM3203199", "GSM3203200", "GSM3203201", "GSM3203202", "GSM3203203", "GSM3203204", "GSM3203205", "GSM3203206", "GSM3203207", "GSM3203208", "GSM3203209", "GSM3203210", "GSM3203211", "GSM3203212", "GSM3203213", "GSM3203214", "GSM3203215", "GSM3203216", "GSM3203217", "GSM3203218", "GSM3203219", "GSM3203220", "GSM3203221", "GSM3203222", "GSM3203223", "GSM3203224", "GSM3203225", "GSM3203226", "GSM3203227", "GSM3203228", "GSM3203229", "GSM3203230", "GSM3203231", "GSM3203232", "GSM3203233", "GSM3203234", "GSM3203235", "GSM3203236", "GSM3203237", "GSM3203238", "GSM3203239", "GSM3203240", "GSM3203241", "GSM3203242", "GSM3203243", "GSM3203244", "GSM3203245", "GSM3203246", "GSM3203247", "GSM3203248", "GSM3203249", "GSM3203250", "GSM3203251", "GSM3203252", "GSM3203253", "GSM3203254", "GSM3203255", "GSM3203256", "GSM3203257", "GSM3203258", "GSM3203259", "GSM3203260", "GSM3203261", "GSM3203262", "GSM3203263", "GSM3203264", "GSM3203265", "GSM3203266", "GSM3203267", "GSM3203268", "GSM3203269", "GSM3203270", "GSM3203271", "GSM3203272", "GSM3203273", "GSM3203274", "GSM3203275", "GSM3203276", "GSM3203277", "GSM3203278", "GSM3203279", "GSM3203280", "GSM3203281", "GSM3203282", "GSM3203283", "GSM3203284", "GSM3203285", "GSM3203286", "GSM3203287", "GSM3203288", "GSM3203289", "GSM3203290", "GSM3203291", "GSM3203292", "GSM3203293", "GSM3203294", "GSM3203295", "GSM3203296", "GSM3203297", "GSM3203298", "GSM3203299", "GSM3203300", "GSM3203301", "GSM3203302", "GSM3203303", "GSM3203304", "GSM3203305", "GSM3203306", "GSM3203307", "GSM3203308", "GSM3203309", "GSM3203310", "GSM3203311", "GSM3203312", "GSM3203313", "GSM3203314", "GSM3203315", "GSM3203316", "GSM3203317", "GSM3203318", "GSM3203319", "GSM3203320", "GSM3203321", "GSM3203322", "GSM3203323", "GSM3203324", "GSM3203325", "GSM3203326", "GSM3203327", "GSM3203328", "GSM3203329", "GSM3203330", "GSM3203331", "GSM3203332", "GSM3203333", "GSM3203334", "GSM3203335", "GSM3203336", "GSM3203337", "GSM3203338", "GSM3203339", "GSM3203340", "GSM3203341", "GSM3203342", "GSM3203343", "GSM3203344", "GSM3203345", "GSM3203346", "GSM3203347", "GSM3203348", "GSM3203349", "GSM3203350", "GSM3203351", "GSM3203352", "GSM3203353", "GSM3203354", "GSM3203355", "GSM3203356", "GSM3203357", "GSM3203358", "GSM3203359", "GSM3203360", "GSM3203361", "GSM3203362", "GSM3203363", "GSM3203364", "GSM3203365", "GSM3203366", "GSM3203367", "GSM3203368", "GSM3203369", "GSM3203370", "GSM3203371", "GSM3203372", "GSM3203373", "GSM3203374", "GSM3203375", "GSM3203376", "GSM3203377", "GSM3203378", "GSM3203379", "GSM3203380", "GSM3203381", "GSM3203382", "GSM3203383", "GSM3203384", "GSM3203385", "GSM3203386", "GSM3203387", "GSM3203388", "GSM3203389", "GSM3203390", "GSM3203391", "GSM3203392", "GSM3203393", "GSM3203394", "GSM3203395", "GSM3203396", "GSM3203397", "GSM3203398", "GSM3203399", "GSM3203400", "GSM3203401", "GSM3203402", "GSM3203403", "GSM3203404", "GSM3203405", "GSM3203406", "GSM3203407", "GSM3203408", "GSM3203409", "GSM3203410", "GSM3203411", "GSM3203412", "GSM3203413", "GSM3203414", "GSM3203415", 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"GSM3204197", "GSM3204198", "GSM3204199", "GSM3204200", "GSM3204201", "GSM3204202", "GSM3204203", "GSM3204204", "GSM3204205", "GSM3204206", "GSM3204207", "GSM3204208", "GSM3204209", "GSM3204210", "GSM3204211", "GSM3204212", "GSM3204213", "GSM3204214", "GSM3204215", "GSM3204216", "GSM3204217", "GSM3204218", "GSM3204219", "GSM3204220", "GSM3204221", "GSM3204222", "GSM3204223", "GSM3204224", "GSM3204225", "GSM3204226", "GSM3204227", "GSM3204228", "GSM3204229", "GSM3204230", "GSM3204231", "GSM3204232", "GSM3204233", "GSM3204234", "GSM3204235", "GSM3204236", "GSM3204237", "GSM3204238", "GSM3204239", "GSM3204240", "GSM3204241", "GSM3204242", "GSM3204243", "GSM3204244", "GSM3204245", "GSM3204246", "GSM3204247", "GSM3204248", "GSM3204249", "GSM3204250", "GSM3204251", "GSM3204252", "GSM3204253", "GSM3204254", "GSM3204255", "GSM3204256", "GSM3204257", "GSM3204258", "GSM3204259", "GSM3204260", "GSM3204261", "GSM3204262", "GSM3204263", "GSM3204264", "GSM3204265", "GSM3204266", "GSM3204267", "GSM3204268", "GSM3204269", "GSM3204270", "GSM3204271", "GSM3204272", "GSM3204273", "GSM3204274", "GSM3204275", "GSM3204276", "GSM3204277", "GSM3204278", "GSM3204279", "GSM3204280", "GSM3204281", "GSM3204282", "GSM3204283", "GSM3204284", "GSM3204285", "GSM3204286", "GSM3204287", "GSM3204288", "GSM3204289", "GSM3204290", "GSM3204291", "GSM3204292", "GSM3204293", "GSM3204294", "GSM3204295", "GSM3204296", "GSM3204297", "GSM3204298", "GSM3204299", "GSM3204300"], "sample_count": 7186, "group_sizes": null, "group_sizes_basis": null, "platform": "18573", "taxon": "Homo sapiens", "title": "Single-cell RNA-seq of melanoma ecosystems reveals sources of T cells exclusion linked to immunotherapy clinical outcomes", "resolution_checked_at": "2026-11-01T18:06:43Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE129845", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE129845", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE129845", "version": null, "note": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM3723357", "GSM3723358", "GSM3723359", "GSM3723360", "GSM3723361"], "sample_count": 5, "group_sizes": null, "group_sizes_basis": null, "platform": "20795;21273", "taxon": "Mus musculus; Homo sapiens", "title": "Single-cell transcriptomic map of the human and mouse bladders", "resolution_checked_at": "2026-11-01T20:16:08Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE131907", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE131907", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE131907", "version": null, "note": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM3827114", "GSM3827115", "GSM3827116", "GSM3827117", "GSM3827118", "GSM3827119", "GSM3827120", "GSM3827121", "GSM3827122", "GSM3827123", "GSM3827124", "GSM3827125", "GSM3827126", "GSM3827127", "GSM3827128", "GSM3827129", "GSM3827130", "GSM3827131", "GSM3827132", "GSM3827133", "GSM3827134", "GSM3827135", "GSM3827136", "GSM3827137", "GSM3827138", "GSM3827139", "GSM3827140", "GSM3827141", "GSM3827142", "GSM3827143", "GSM3827144", "GSM3827145", "GSM3827146", "GSM3827147", "GSM3827148", "GSM3827149", "GSM3827150", "GSM3827151", "GSM3827152", "GSM3827153", "GSM3827154", "GSM3827155", "GSM3827156", "GSM3827157", "GSM3827158", "GSM3827159", "GSM3827160", "GSM3827161", "GSM3827162", "GSM3827163", "GSM3827164", "GSM3827165", "GSM3827166", "GSM3827167", "GSM3827168", "GSM3827169", "GSM3827170", "GSM3827171"], "sample_count": 58, "group_sizes": null, "group_sizes_basis": null, "platform": "16791", "taxon": "Homo sapiens", "title": "Single cell RNA sequencing of lung adenocarcinoma", "resolution_checked_at": "2026-11-01T18:06:43Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE149614", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE149614", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE149614", "version": null, "note": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM4505944", "GSM4505945", "GSM4505946", "GSM4505947", "GSM4505948", "GSM4505949", "GSM4505950", "GSM4505951", "GSM4505952", "GSM4505953", "GSM4505954", "GSM4505955", "GSM4505956", "GSM4505957", "GSM4505958", "GSM4505959", "GSM4505960", "GSM4505961", "GSM4505962", "GSM4505963", "GSM4505964"], "sample_count": 21, "group_sizes": null, "group_sizes_basis": null, "platform": "24676", "taxon": "Homo sapiens", "title": "A Single-Cell Atlas of the Multicellular Ecosystem of Primary and Metastatic Hepatocellular Carcinoma", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE164690", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE164690", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE164690", "version": null, "note": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM5017021", "GSM5017022", "GSM5017023", "GSM5017024", "GSM5017025", "GSM5017026", "GSM5017027", "GSM5017028", "GSM5017029", "GSM5017030", "GSM5017031", "GSM5017032", "GSM5017033", "GSM5017034", "GSM5017035", "GSM5017036", "GSM5017037", "GSM5017038", "GSM5017039", "GSM5017040", "GSM5017041", "GSM5017042", "GSM5017043", "GSM5017044", "GSM5017045", "GSM5017046", "GSM5017047", "GSM5017048", "GSM5017049", "GSM5017050", "GSM5017051", "GSM5017052", "GSM5017053", "GSM5017054", "GSM5017055", "GSM5017056", "GSM5017057", "GSM5017058", "GSM5017059", "GSM5017060", "GSM5017061", "GSM5017062", "GSM5017063", "GSM5017064", "GSM5017065", "GSM5017066", "GSM5017067", "GSM5017068", "GSM5017069", "GSM5017070", "GSM5017071"], "sample_count": 51, "group_sizes": null, "group_sizes_basis": null, "platform": "18573", "taxon": "Homo sapiens", "title": "Investigating Immune and Non-Immune Cell Interactions in Head and Neck Tumors by Single-Cell RNA Sequencing", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE176078", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE176078", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE176078", "version": null, "note": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM5354513", "GSM5354514", "GSM5354515", "GSM5354516", "GSM5354517", "GSM5354518", "GSM5354519", "GSM5354520", "GSM5354521", "GSM5354522", "GSM5354523", "GSM5354524", "GSM5354525", "GSM5354526", "GSM5354527", "GSM5354528", "GSM5354529", "GSM5354530", "GSM5354531", "GSM5354532", "GSM5354533", "GSM5354534", "GSM5354535", "GSM5354536", "GSM5354537", "GSM5354538"], "sample_count": 26, "group_sizes": null, "group_sizes_basis": null, "platform": "18573", "taxon": "Homo sapiens", "title": "A single-cell and spatially resolved atlas of human breast cancers", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE183904", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE183904", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE183904", "version": null, "note": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM5573466", "GSM5573467", "GSM5573468", "GSM5573469", "GSM5573470", "GSM5573471", "GSM5573472", "GSM5573473", "GSM5573474", "GSM5573475", "GSM5573476", "GSM5573477", "GSM5573478", "GSM5573479", "GSM5573480", "GSM5573481", "GSM5573482", "GSM5573483", "GSM5573484", "GSM5573485", "GSM5573486", "GSM5573487", "GSM5573488", "GSM5573489", "GSM5573490", "GSM5573491", "GSM5573492", "GSM5573493", "GSM5573494", "GSM5573495", "GSM5573496", "GSM5573497", "GSM5573498", "GSM5573499", "GSM5573500", "GSM5573501", "GSM5573502", "GSM5573503", "GSM5573504", "GSM5573505"], "sample_count": 40, "group_sizes": null, "group_sizes_basis": null, "platform": "24676", "taxon": "Homo sapiens", "title": "Single-cell atlas of lineage states, tumor microenvironment and subtype specific expression programs in gastric cancer", "resolution_checked_at": "2026-11-01T19:09:46Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:E-MTAB-11948 not downloaded", "asset:data:geo:E-MTAB-11948 licence not read", "asset:data:geo:E-MTAB-8107 not downloaded", "asset:data:geo:E-MTAB-8107 licence not read", "asset:data:geo:GSE115978 not downloaded", "asset:data:geo:GSE115978 licence not read", "asset:data:geo:GSE129845 not downloaded", "asset:data:geo:GSE129845 licence not read", "asset:data:geo:GSE131907 not downloaded", "asset:data:geo:GSE131907 licence not read", "asset:data:geo:GSE149614 not downloaded", "asset:data:geo:GSE149614 licence not read", "asset:data:geo:GSE164690 not downloaded", "asset:data:geo:GSE164690 licence not read", "asset:data:geo:GSE176078 not downloaded", "asset:data:geo:GSE176078 licence not read", "asset:data:geo:GSE183904 not downloaded", "asset:data:geo:GSE183904 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Here, we introduce scSurv, combining a Cox proportional hazards model with a deep generative model of single-cell transcriptome, to estimate individual cellular contributions to clinical outcomes."}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE129845", "GSE115978", "GSE131907", "GSE176078", "GSE132465 and GSE144735", "GSE164690", "GSE149614", "GSE183904", "E-MTAB-11948", "E-MTAB-8107"], "resolved_accessions": ["GSE129845", "GSE115978", "GSE131907", "GSE176078", "GSE164690", "GSE149614", "GSE183904", "E-MTAB-11948", "E-MTAB-8107"], "statements": ["The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054). The single-cell RNA sequencing datasets used in this study are available from the Gene Expression Omnibus (GEO) under accession numbers GSE129845 (kidney cancer)(Li et al. 2022b), GSE115978 (melanoma)(Jerby-Arnon et al. 2018), GSE129845 (bladder cancer)(Yu et al. 2019), GSE131907 (lung adenocarcinoma)(Kim et al. 2020), GSE176078 (breast cancer)(Wu et al. 2021), GSE132465 and GSE144735 (colorectal cancer)(Lee et al. 2020), GSE164690 (head and neck cancer)(Kürten et al. 2021), GSE149614 (hepatocellular carcinoma)(Lu et al. 2022), and GSE183904 (gastric cancer)(Kumar et al. 2022); from ArrayExpress under accession numbers E-MTAB-11948 (cervical cancer)(Li et al. 2022a) and E-MTAB-8107 (lung squamous cell carcinoma)(Qian et al. 2020); from Cell x Gene Explorer (Collection ID: 4796c91c-9d8f-4692-be43-347b1727f9d8) for ovarian cancer(Vázquez-García et al. 2022); and from COVID-19 Cell Atlas (https://covid19cellatlas.org) for COVID-19 PBMCs. Bulk RNA sequencing data and clinical information from TCGA are available from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov/). The bulk RNA-seq and clinical outcome data from the IMPACC cohort used in this study are accessible via the ImmPort database (https://www.immport.org) with a data access request."], "basis": "The paper names GSE129845, GSE115978, GSE131907, GSE176078, GSE164690, GSE149614, GSE183904, E-MTAB-11948, E-MTAB-8107 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["cox_ph"], "assets": ["source:pmid:41429574", "data:geo:E-MTAB-11948"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:E-MTAB-11948"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T20:08:51Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 10915, "completion_tokens": 6940, "cached_tokens": 264}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:41429574", "type": "paper", "label": "pmid:41429574"}, {"id": "source:pmid:41429574", "type": "manuscript", "label": "PMID 41429574 full text"}, {"id": "data:geo:E-MTAB-11948", "type": "dataset", "label": "GEO E-MTAB-11948"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:41429574", "type": "paper", "label": "pmid:41429574"}, {"id": "source:pmid:41429574", "type": "manuscript", "label": "PMID 41429574 full text"}, {"id": "data:geo:E-MTAB-11948", "type": "dataset", "label": "GEO E-MTAB-11948"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-41429574", "type": "extraction", "used": ["source:pmid:41429574"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-E-MTAB-11948", "type": "accession_resolution", "used": ["data:geo:E-MTAB-11948"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:41429574", "parent_hash": "sha256:15af76e7eee970663a436ff3914ee93b9bcd093e01233c6fa96190afc6edf81c", "fork_of": null, "generation": 1}, "gaps": ["asset:data:geo:E-MTAB-11948 licence not read", "asset:data:geo:E-MTAB-11948 not downloaded", "asset:data:geo:E-MTAB-8107 licence not read", "asset:data:geo:E-MTAB-8107 not downloaded", "asset:data:geo:GSE115978 licence not read", "asset:data:geo:GSE115978 not downloaded", "asset:data:geo:GSE129845 licence not read", "asset:data:geo:GSE129845 not downloaded", "asset:data:geo:GSE131907 licence not read", "asset:data:geo:GSE131907 not downloaded", "asset:data:geo:GSE149614 licence not read", "asset:data:geo:GSE149614 not downloaded", "asset:data:geo:GSE164690 licence not read", "asset:data:geo:GSE164690 not downloaded", "asset:data:geo:GSE176078 licence not read", "asset:data:geo:GSE176078 not downloaded", "asset:data:geo:GSE183904 licence not read", "asset:data:geo:GSE183904 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Here, we introduce scSurv, combining a Cox proportional hazards model with a deep generative model of single-cell transcriptome, to estimate individual cellular contributions to clinical outcomes."], "order_basis": "analysis_only", "id": "assay:1"}]},"meta":{"api_version":"v1","automation_ladder_snapshot":"ba34b49490d9bfaf","automation_ladder_caveats":["Method extraction is rule-based and has no hand-judged accuracy sample. Evidence bands order textual support; method agreement intervals are null (n=0), never probabilities. Work-type validation does not validate methods.","Operation coverage describes only explicitly named methods. It does not prove a complete protocol, compatible parameters, successful compilation or re-execution. Unrecognised or ambiguous methods require review.","Data reachability is a textual accession or public-data statement. No dataset was downloaded or checked for access, completeness or licence.","Capabilities are planning states seeded from the dated equipment register. No bench ownership, completed quote or partner booking is inferred. Procurement counts are dependencies, not guaranteed replications or financial returns.","Tier and blocker counts are deterministic assessments of this corpus, not measured agreement. R3 is reserved for procurement; unresolved methods and data require human work (R4). The most restrictive axis wins, with capability, method, data as tie-breaks. Resolving one blocker can leave another at the same tier."],"engine":"corpus_engine","engine_provider":"rule_based_v1+lex99e1195c7d6f","run_id":"run-20261023T122449232913","source":"esearch","source_detail":"PubMed mirror biomed_pubmed (read-only)","run_status":"complete","imported_at":"2026-11-03T20:16:52+00:00","generated_at":"2026-11-04T00:31:56+00:00","total_papers":5529,"total_assays_tracked":29,"automatable_assay_families":6,"validated":true,"caveat_count":9,"blocking_caveats":5,"caveats":[{"code":"low_evidence_dominates","basis":["4,152 of 5,529 classifications (75.1%) matched no cue evidence and sit at the 0.05 floor.","34 of 230 data_only calls (14.8%) are in that group."],"claim":"Work type and confidence bands","gloss":"Most records were classified from their title and framing alone, with assay-cue coverage at zero.","detail":"Most classifications in this run rest on no matched evidence at all. At the evidence floor the work type comes from title framing and a fixed prior, not from anything in the paper, so the published work-type split should be read as a rough triage signal rather than a measured distribution. The impact is bounded but not removed: since 2026-10-23 the engine excludes floor-confidence records from the shortlist entirely and publishes them separately as held out, so the recommendation is unaffected even though the census is.","status":"unverified","severity":"high"},{"code":"runtime_is_modelled","basis":["Runtime is summed from published per-assay hour figures. Timing awaits the first executed replication.","4,407 of 5,529 records (79.7%) model to 0.00 hours because no assay was matched, which the ranking then reads as \"cheapest\".","0 of 10 shortlisted records carry a 0.00-hour estimate."],"claim":"Estimated replication runtime","gloss":"The hour figures are estimates built from assay mentions; timing awaits the first executed replication.","detail":"The hour figures are a cost model derived from the bench steps implied by each matched assay family. The first executed replication will supply measured timing. Records without an assay match currently receive a zero-hour model value.","status":"unverified","severity":"high"},{"code":"signal_score_without_citations","basis":["5,529 of 5,529 records (100.0%) have no citation count from the source metadata."],"claim":"Signal score","gloss":"The signal score uses publication-type weight because the mirror supplied zero citation counts.","detail":"The source supplied no citation counts for any record in this run, so the signal score is publication-type weight only. The citation term of the ranking is inert here, and the shortlist is ordered by publication type alone.","status":"unverified","severity":"high"},{"code":"abstract_absent","basis":["1,667 of 5,529 records (30.2%) carry no abstract at all."],"claim":"Evidence base for classification","gloss":"Some records contain a title and publication type only, defining the available classification evidence.","detail":"Where the mirror contains a title and publication types only, those fields define the classifier evidence. A methods section is required for fuller automated and human review.","status":"unverified","severity":"medium"},{"code":"classifier_agreement_measured","basis":["Published two-way decision agreement 77.7% (310 of 399 decidable records) from a stratified hand-check of 438 real records.","Three-way diagnostic agreement 73.9% (288 of 390 decidable records).","data_only agreement 75.2% (100 of 133 decidable).","48 record(s) could not be decided from title and abstract and were excluded from the denominator.","56 analysis-only records were published under another work type, so the data_only share is not an upper bound."],"claim":"Published automatable decision","gloss":"This figure has been checked against a human reading the same papers, so we know how often it is right.","detail":"The published automatable / not-automatable distribution comes from a rule-based classifier that was hand-checked against a fixed ground-truth definition. The agreement rates below are measured, not estimated. The three-way work type remains a diagnostic and is reported separately.","status":"measured","severity":"high"},{"code":"llm_comparison_not_measured","basis":["rule_based_v1+lex99e1195c7d6f produced 5,529 of 5,529 classifications.","Measured on 438 labelled records; these are RULE-BASED figures, not model results."],"claim":"Rule-based versus LLM agreement","gloss":"Every number here is the rule engine’s own. Model comparison begins when a working API credential is connected and measured.","detail":"The published two-way decision agreed with a human reading on 310 of 399 decidable records (77.7%). The diagnostic three-way label agreed on 288 of 390 decidable records (73.9%). Every percentage in this run belongs to the rule engine. Model comparison begins when a working API credential is connected and measured.","status":"not_measured","severity":"high"},{"code":"confidence_is_a_band","basis":["low band: 135 of 210 hand-judged records were correct, 64.3% [57.6, 70.5] (95% CI).","medium band: 80 of 104 hand-judged records were correct, 76.9% [68.0, 84.0] (95% CI).","high band: 73 of 76 hand-judged records were correct, 96.0% [89.0, 98.7] (95% CI).","A fitted calibrated probability was built, measured and withdrawn: it overstated held-out accuracy and reorders nothing."],"claim":"Confidence band and evidence score","gloss":"The confidence band carries a measured accuracy interval; 0.85 represents relative rank strength.","detail":"Confidence on this run is a BAND plus its measured accuracy interval. The number stored alongside each record is a monotone evidence score that orders records; 0.85 represents relative rank strength. A fitted probability was withdrawn after it overstated held-out accuracy. Threshold on the band.","status":"measured","severity":"medium"},{"code":"three_way_split_is_diagnostic","basis":["The corpus is published at the two-way decision: automatable or not-automatable. The three-way split (data_only / physical / mixed) is published as a diagnostic with its measured reliability attached, not as a claim, because the rule engine's `mixed` call cannot be defended.","The engine called 22 record(s) mixed; 10 matched the human judgement (45.5%, 95% CI 26.9-65.3).","The engine's `mixed` call is right on 10/22 hand-judged records (45.5%, 95% CI 26.9%-65.3%); a constant `physical` guess scores 36.4%.","The engine's `mixed` call does not reliably beat a constant `physical` guess on the hand-judged records it labels mixed.","The sign of that difference flips between two independent samples, so the three-way refinement is not demonstrably informative.","The mixed stratum contributes a disproportionate share of errors relative to its size.","At title-only depth the physical/mixed split collapses: a title says that work was done, not whether it was also analysed."],"claim":"The published decision is two-way","gloss":"The three-way split is shown for diagnosis only. The published split is two ways.","detail":"Count and filter the corpus on automatable versus not-automatable. The data_only / physical / mixed split remains an internal engine diagnostic because the mixed call has lower measured reliability.","status":"measured","severity":"medium"},{"code":"automatable_flag_unproven","basis":["6 of 29 assay families are marked automatable now: meta_analysis, machine_learning, survival_analysis, pca, molecular_docking, differential_expression.","The flag is a rule over assay family and work type; validation begins with the first executed replication.","It inherits the 75.2% data_only agreement rate, because the flag requires the record to be analysis-only."],"claim":"Automatable now","gloss":"This flag marks assay families the rules classify as data-only. The first executed replication will validate it.","detail":"This flag marks families the rules consider replicable from data alone. Its validity depends on the analysis-only classification and will be measured through an executed replication.","status":"unverified","severity":"medium"}],"confidence_policy":"band_with_measured_interval","confidence_contract":{"policy":"band_with_measured_interval","summary":"Confidence is reported as a BAND with a measured accuracy interval. The raw evidence score supplies monotone ordering. A fitted point estimate was withdrawn after it overstated held-out accuracy.","evidence_score":"A monotone evidence score in [0,1] built from cue mass, axis separation and text coverage. Use it to order records. Interpret 0.85 as relative rank strength.","confidence_band":"low | medium | high. Consumers threshold on this value.","band_accuracy":"Wilson 95% interval on the measured agreement of the hand-judged records in this band.","calibrated_confidence":"WITHDRAWN. Reintroduction requires held-out evidence demonstrating reliable estimates across every bin."},"band_accuracy":{"low":{"n":210,"low":0.576,"band":"low","high":0.7046,"agree":135,"accuracy":0.6429},"high":{"n":76,"low":0.8903,"band":"high","high":0.9865,"agree":73,"accuracy":0.9605},"medium":{"n":104,"low":0.6795,"band":"medium","high":0.8397,"agree":80,"accuracy":0.7692}},"provider":"rule_based_v1+lex99e1195c7d6f","lexicon_id":"99e1195c7d6f","contract_published_at":"2026-10-23T12:25:29.022232+00:00","confidence_is_band":true,"confidence_is_probability":false,"decision_taxonomy":"two_way","decidable_fraction_two_way":0.8854,"decidable_fraction_two_way_low":0.8565,"decidable_fraction_two_way_high":0.9143,"decidable_fraction_three_way":0.8586,"decidable_fraction_three_way_low":0.8287,"decidable_fraction_three_way_high":0.8884,"decidable_population":5529,"validation_sample_size":438,"three_way_cost_fraction":0.0268,"three_way_cost_records":148,"decision_counts":{"automatable":230,"not_automatable":5299},"decision_split":{"automatable":{"count":230,"share":0.04159884246699222},"not_automatable":{"count":5299,"share":0.9584011575330078}},"diagnostic_work_type_counts":{"mixed":24,"physical":5275,"data_only":230}}}