← All .science files
pmid:36685978
A novel pyroptosis scoring model was associated with the prognosis and immune microenvironment of esophageal squamous cell carcinoma.
Zhan-Fei Zhang
Frontiers in genetics · 2022 doi:10.3389/fgene.2022.1034606
Paper
complete
Experiment
complete
Data
partial
Analysis
partial
Execution
absent
Execution evidence has not yet been added to this .science file. Explore its methods, data and open questions to plan the next step.
Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
paper object · 10 fields
authors array · 1 item
claims array · 3 items
[0] object · 6 fields
evidence array · 1 item
[0] object · 3 fields
[1] object · 6 fields
evidence array · 1 item
[0] object · 3 fields
[2] object · 6 fields
evidence array · 2 items
[0] object · 3 fields
[1] object · 3 fields
gaps array · 0 items
experiment object · 8 fields
steps array · 3 items
[0] object · 13 fields
parameters object · 0 fields
inputs array · 1 item
outputs array · 1 item
instruments array · 0 items
reagents array · 0 items
[1] object · 13 fields
parameters object · 0 fields
inputs array · 1 item
outputs array · 1 item
instruments array · 0 items
reagents array · 0 items
[2] object · 13 fields
parameters object · 0 fields
inputs array · 1 item
outputs array · 1 item
instruments array · 0 items
reagents array · 0 items
materials array · 0 items
instruments array · 0 items
reagents array · 0 items
conditions object · 0 fields
gaps array · 0 items
data object · 3 fields
assets array · 2 items
[0] object · 15 fields
structure object · 4 fields
[1] object · 15 fields
structure object · 15 fields
sample_accessions array · 358 items
gaps array · 2 items
analysis object · 4 fields
methods array · 5 items
[0] object · 10 fields
dsl_operations array · 1 item
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
evidence object · 3 fields
[1] object · 10 fields
dsl_operations array · 0 items
missing_operations array · 1 item
parameters object · 0 fields
data_shapes array · 1 item
[2] object · 10 fields
dsl_operations array · 1 item
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[3] object · 10 fields
dsl_operations array · 3 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[4] object · 10 fields
dsl_operations array · 1 item
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
targets array · 0 items
gaps array · 1 item
capability object · 3 fields
requirements array · 1 item
[0] object · 6 fields
assay_families array · 9 items
gaps array · 0 items
readiness object · 8 fields
axes object · 3 fields
method object · 5 fields
required_operations array · 1 item
missing_operations array · 0 items
capability object · 4 fields
data object · 6 fields
accessions array · 1 item
resolved_accessions array · 1 item
statements array · 1 item
can_run object · 3 fields
dsl_operations array · 1 item
assets array · 2 items
steps array · 1 item
must_build object · 5 fields
dsl_operations array · 0 items
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
gaps array · 0 items
review object · 5 fields
machine_critique object · 5 fields
reader object · 5 fields
evidence_check object · 2 fields
usage object · 3 fields
stages array · 1 item
[0] object · 4 fields
gaps array · 3 items
provenance object · 7 fields
entities array · 3 items
activities array · 3 items
[0] object · 4 fields
used array · 3 items
[0] object · 3 fields
[1] object · 3 fields
[2] object · 3 fields
[1] object · 4 fields
agents array · 2 items
lineage object · 4 fields
gaps array · 7 items
assays array · 1 item
[0] object · 11 fields
required_operations array · 1 item
source_hashes object · 1 field
evidence array · 1 item
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36685978", "kind": "science-record", "revision": 3, "content_hash": "sha256:b3655917c2ce19d4c709f53703e3076f933591e2afe37d2eab2042c0315f3412", "created_at": "2026-11-01T19:01:14Z", "updated_at": "2026-11-01T22:08:36Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A novel pyroptosis scoring model was associated with the prognosis and immune microenvironment of esophageal squamous cell carcinoma.", "doi": "10.3389/fgene.2022.1034606", "pmid": "36685978", "authors": ["Zhan-Fei Zhang"], "journal": "Frontiers in genetics", "year": 2022, "abstract": "The phenotype of pyroptosis has been extensively studied in a variety of tumors, but the relationship between pyroptosis and esophageal squamous cell carcinoma (ESCC) remains unclear. Here, 22 pyroptosis genes were downloaded from the website of Gene Set Enrichment Analysis (GSEA), 79 esophageal squamous cell carcinoma samples and GSE53625 containing 179 pairs of esophageal squamous cell carcinoma samples were collected from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), respectively. Then, pyroptosis subtypes of esophageal squamous cell carcinoma were obtained by cluster analysis according to the expression difference of pyroptosis genes, and a pyroptosis scoring model was constructed by the pyroptosis-related genes screened from different pyroptosis subtypes. Time-dependent receiver operator characteristic (timeROC) curves and the area under the curve (AUC) values were used to evaluate the prognostic predictive accuracy of the pyroptosis scoring model. Kaplan-Meier method with log-rank test were conducted to analyze the impact of the pyroptosis scoring model on overall survival (OS) of patients with esophageal squamous cell carcinoma. Nomogram models and calibration curves were used to further confirm the effect of the pyroptosis scoring model on prognosis. Meanwhile, CIBERSORTx and ESTIMATE algorithm were applied to calculate the influence of the pyroptosis scoring model on esophageal squamous cell carcinoma immune microenvironment. Our findings revealed that the pyroptosis scoring model established by the pyroptosis-related genes was associated with the prognosis and immune microenvironment of esophageal squamous cell carcinoma, which can be used as a biomarker to predict the prognosis and act as a potential target for the treatment of esophageal squamous cell carcinoma.", "claims": [{"id": "claim-method", "statement": "Time-dependent receiver operating characteristic (timeROC) curves were applied to assess the prognostic predictive accuracy at 1-year, 2-year, 3-year and 5-year by the timeROC R package. In addition, Kaplan-Meier method with log-rank test were conducted to evaluate the impact of the pyroptosis scoring model on the OS of ESCC.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36685978", "locator": "sections[7] \"2.5 Construction and evaluation of pyroptosis scoring model\" paragraph 2", "quote": "Time-dependent receiver operating characteristic (timeROC) curves were applied to assess the prognostic predictive accuracy at 1-year, 2-year, 3-year and 5-year by the timeROC R package. In addition, Kaplan-Meier method with log-rank test were conducted to evaluate the impact of the pyroptosis scoring model on the OS of ESCC."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36685978", "locator": "sections[20] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A pyroptosis scoring model was associated with the prognosis and immune microenvironment of esophageal squamous cell carcinoma and had prognostic predictive accuracy across 1-, 2-, 3-, and 5-year time points.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36685978", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Our findings revealed that the pyroptosis scoring model established by the pyroptosis-related genes was associated with the prognosis and immune microenvironment of esophageal squamous cell carcinoma, which can be used as a biomarker to predict the prognosis and act as a potential target for the treatment of esophageal squamous cell carcinoma."}, {"asset": "source:pmid:36685978", "locator": "sections[7] \"2.5 Construction and evaluation of pyroptosis scoring model\" paragraph 2", "quote": "Time-dependent receiver operating characteristic (timeROC) curves were applied to assess the prognostic predictive accuracy at 1-year, 2-year, 3-year and 5-year by the timeROC R package."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A pyroptosis scoring model was associated with the prognosis and immune microenvironment of esophageal squamous cell carcinoma and had prognostic predictive accuracy across 1-, 2-, 3-, and 5-year time points.", "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:36685978"], "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:GSE53625"], "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:GSE53625"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36685978", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fgene.2022.1034606", "sha256": "sha256:de59680f4aadc97343b8cbf55b8ce61c5119ac58cf5a1c93ee375636ffed5b7e", "bytes": 37699, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fgene.2022.1034606", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9845255", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE53625", "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=GSE53625", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE53625", "version": null, "note": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1296956", "GSM1296957", "GSM1296958", "GSM1296959", "GSM1296960", "GSM1296961", "GSM1296962", "GSM1296963", "GSM1296964", "GSM1296965", "GSM1296966", "GSM1296967", "GSM1296968", "GSM1296969", "GSM1296970", "GSM1296971", "GSM1296972", "GSM1296973", "GSM1296974", "GSM1296975", "GSM1296976", "GSM1296977", "GSM1296978", "GSM1296979", "GSM1296980", "GSM1296981", "GSM1296982", "GSM1296983", "GSM1296984", "GSM1296985", "GSM1296986", "GSM1296987", "GSM1296988", "GSM1296989", "GSM1296990", "GSM1296991", "GSM1296992", "GSM1296993", "GSM1296994", "GSM1296995", "GSM1296996", "GSM1296997", "GSM1296998", "GSM1296999", "GSM1297000", "GSM1297001", "GSM1297002", "GSM1297003", "GSM1297004", "GSM1297005", "GSM1297006", "GSM1297007", "GSM1297008", "GSM1297009", "GSM1297010", "GSM1297011", "GSM1297012", "GSM1297013", "GSM1297014", "GSM1297015", "GSM1297016", "GSM1297017", "GSM1297018", "GSM1297019", "GSM1297020", "GSM1297021", "GSM1297022", "GSM1297023", "GSM1297024", "GSM1297025", "GSM1297026", "GSM1297027", "GSM1297028", "GSM1297029", "GSM1297030", "GSM1297031", "GSM1297032", "GSM1297033", "GSM1297034", "GSM1297035", "GSM1297036", "GSM1297037", "GSM1297038", "GSM1297039", "GSM1297040", "GSM1297041", "GSM1297042", "GSM1297043", "GSM1297044", "GSM1297045", "GSM1297046", "GSM1297047", "GSM1297048", "GSM1297049", "GSM1297050", "GSM1297051", "GSM1297052", "GSM1297053", "GSM1297054", "GSM1297055", "GSM1297056", "GSM1297057", "GSM1297058", "GSM1297059", "GSM1297060", "GSM1297061", "GSM1297062", "GSM1297063", "GSM1297064", "GSM1297065", "GSM1297066", "GSM1297067", "GSM1297068", "GSM1297069", "GSM1297070", "GSM1297071", "GSM1297072", "GSM1297073", "GSM1297074", "GSM1297075", "GSM1297076", "GSM1297077", "GSM1297078", "GSM1297079", "GSM1297080", "GSM1297081", "GSM1297082", "GSM1297083", "GSM1297084", "GSM1297085", "GSM1297086", "GSM1297087", "GSM1297088", "GSM1297089", "GSM1297090", "GSM1297091", "GSM1297092", "GSM1297093", "GSM1297094", "GSM1297095", "GSM1297096", "GSM1297097", "GSM1297098", "GSM1297099", "GSM1297100", "GSM1297101", "GSM1297102", "GSM1297103", "GSM1297104", "GSM1297105", "GSM1297106", "GSM1297107", "GSM1297108", "GSM1297109", "GSM1297110", "GSM1297111", "GSM1297112", "GSM1297113", "GSM1297114", "GSM1297115", "GSM1297116", "GSM1297117", "GSM1297118", "GSM1297119", "GSM1297120", "GSM1297121", "GSM1297122", "GSM1297123", "GSM1297124", "GSM1297125", "GSM1297126", "GSM1297127", "GSM1297128", "GSM1297129", "GSM1297130", "GSM1297131", "GSM1297132", "GSM1297133", "GSM1297134", "GSM1297135", "GSM1297136", "GSM1297137", "GSM1297138", "GSM1297139", "GSM1297140", "GSM1297141", "GSM1297142", "GSM1297143", "GSM1297144", "GSM1297145", "GSM1297146", "GSM1297147", "GSM1297148", "GSM1297149", "GSM1297150", "GSM1297151", "GSM1297152", "GSM1297153", "GSM1297154", "GSM1297155", "GSM1297156", "GSM1297157", "GSM1297158", "GSM1297159", "GSM1297160", "GSM1297161", "GSM1297162", "GSM1297163", "GSM1297164", "GSM1297165", "GSM1297166", "GSM1297167", "GSM1297168", "GSM1297169", "GSM1297170", "GSM1297171", "GSM1297172", "GSM1297173", "GSM1297174", "GSM1297175", "GSM1297176", "GSM1297177", "GSM1297178", "GSM1297179", "GSM1297180", "GSM1297181", "GSM1297182", "GSM1297183", "GSM1297184", "GSM1297185", "GSM1297186", "GSM1297187", "GSM1297188", "GSM1297189", "GSM1297190", "GSM1297191", "GSM1297192", "GSM1297193", "GSM1297194", "GSM1297195", "GSM1297196", "GSM1297197", "GSM1297198", "GSM1297199", "GSM1297200", "GSM1297201", "GSM1297202", "GSM1297203", "GSM1297204", "GSM1297205", "GSM1297206", "GSM1297207", "GSM1297208", "GSM1297209", "GSM1297210", "GSM1297211", "GSM1297212", "GSM1297213", "GSM1297214", "GSM1297215", "GSM1297216", "GSM1297217", "GSM1297218", "GSM1297219", "GSM1297220", "GSM1297221", "GSM1297222", "GSM1297223", "GSM1297224", "GSM1297225", "GSM1297226", "GSM1297227", "GSM1297228", "GSM1297229", "GSM1297230", "GSM1297231", "GSM1297232", "GSM1297233", "GSM1297234", "GSM1297235", "GSM1297236", "GSM1297237", "GSM1297238", "GSM1297239", "GSM1297240", "GSM1297241", "GSM1297242", "GSM1297243", "GSM1297244", "GSM1297245", "GSM1297246", "GSM1297247", "GSM1297248", "GSM1297249", "GSM1297250", "GSM1297251", "GSM1297252", "GSM1297253", "GSM1297254", "GSM1297255", "GSM1297256", "GSM1297257", "GSM1297258", "GSM1297259", "GSM1297260", "GSM1297261", "GSM1297262", "GSM1297263", "GSM1297264", "GSM1297265", "GSM1297266", "GSM1297267", "GSM1297268", "GSM1297269", "GSM1297270", "GSM1297271", "GSM1297272", "GSM1297273", "GSM1297274", "GSM1297275", "GSM1297276", "GSM1297277", "GSM1297278", "GSM1297279", "GSM1297280", "GSM1297281", "GSM1297282", "GSM1297283", "GSM1297284", "GSM1297285", "GSM1297286", "GSM1297287", "GSM1297288", "GSM1297289", "GSM1297290", "GSM1297291", "GSM1297292", "GSM1297293", "GSM1297294", "GSM1297295", "GSM1297296", "GSM1297297", "GSM1297298", "GSM1297299", "GSM1297300", "GSM1297301", "GSM1297302", "GSM1297303", "GSM1297304", "GSM1297305", "GSM1297306", "GSM1297307", "GSM1297308", "GSM1297309", "GSM1297310", "GSM1297311", "GSM1297312", "GSM1297313"], "sample_count": 358, "group_sizes": null, "group_sizes_basis": null, "platform": "18109", "taxon": "Homo sapiens", "title": "LncRNA profile study reveals a three-lncRNA signature associated with the survival of esophageal squamous cell carcinoma patients", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE53625 not downloaded", "asset:data:geo:GSE53625 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Time-dependent receiver operating characteristic (timeROC) curves were applied to assess the prognostic predictive accuracy at 1-year, 2-year, 3-year and 5-year by the timeROC R package. In addition, Kaplan-Meier method with log-rank test were conducted to evaluate the impact of the pyroptosis scoring model on the OS of ESCC."}}, {"id": "method-2", "family": "group_comparison", "specific": "mann_whitney", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_mann_whitney"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Mann-Whitney"}}, {"id": "method-3", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Kaplan-Meier"}}, {"id": "method-4", "family": "differential_expression", "specific": "deseq2", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 0.8, "band": "high", "quote": "DESeq2"}}, {"id": "method-5", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "pathway enrichment"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor"]}, "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": ["logrank_test"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: log_rank_test."}, "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": ["GSE53625"], "resolved_accessions": ["GSE53625"], "statements": ["The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material."], "basis": "The paper names GSE53625 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": ["logrank_test"], "assets": ["source:pmid:36685978", "data:geo:GSE53625"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE53625"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:24:29Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 12060, "completion_tokens": 1759, "cached_tokens": 256}}, "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:36685978", "type": "paper", "label": "pmid:36685978"}, {"id": "source:pmid:36685978", "type": "manuscript", "label": "PMID 36685978 full text"}, {"id": "data:geo:GSE53625", "type": "dataset", "label": "GEO GSE53625"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36685978", "type": "paper", "label": "pmid:36685978"}, {"id": "source:pmid:36685978", "type": "manuscript", "label": "PMID 36685978 full text"}, {"id": "data:geo:GSE53625", "type": "dataset", "label": "GEO GSE53625"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36685978", "type": "extraction", "used": ["source:pmid:36685978"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE53625", "type": "accession_resolution", "used": ["data:geo:GSE53625"], "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:36685978", "parent_hash": "sha256:bd54c7c5244561cfa98c37179a2e923edef168465cec35be795bcdb98f1987c6", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE53625 licence not read", "asset:data:geo:GSE53625 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["logrank_test"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Time-dependent receiver operating characteristic (timeROC) curves were applied to assess the prognostic predictive accuracy at 1-year, 2-year, 3-year and 5-year by the timeROC R package. In addition, Kaplan-Meier method with log-rank test were conducted to evaluate the impact of the pyroptosis scoring model on the OS of ESCC."], "order_basis": "analysis_only", "id": "assay:1"}]}