Assessment of risk based on variant pathways and establishment of an artificial neural network model of thyroid cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31138213", "kind": "science-record", "revision": 8, "content_hash": "sha256:de39fd9804ed6a4d8c0463bb9c29a503dd0e70afe1d6793757ed4500a5011c79", "created_at": "2026-11-01T15:40:45Z", "updated_at": "2026-11-01T22:43:59Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Assessment of risk based on variant pathways and establishment of an artificial neural network model of thyroid cancer.", "doi": "10.1186/s12881-019-0829-4", "pmid": "31138213", "authors": ["Yinlong Zhao", "Lingzhi Zhao", "Tiezhu Mao", "Lili Zhong"], "journal": "BMC medical genetics", "year": 2019, "abstract": "BACKGROUND: This study aimed to establish an artificial neural network (ANN) model based on variant pathways to predict the risk of thyroid cancer.\nMETHODS: The RNASeq data of 482 thyroid cancer samples were downloaded from the TCGA database. The samples were divided into low-risk and high-risk groups, followed by identification of differentially expressed genes (DEGs). Co-expression analysis and pathway enrichment analysis were then performed. The variant pathways were screened according to the functional deviation score of each pathway, and an ANN model was established. Finally, the efficiency of the ANN model for risk assessment was validated by survival analysis and analysis of an independent microarray dataset (GSE34289) for thyroid cancer.\nRESULTS: In total, 190 DEGs (85 up-regulated and 105 down-regulated) were identified between the low-risk and high-risk groups. Ten risk-related variant pathways were identified between the low-risk and high-risk groups, which were related to inflammatory and immune responses. Based on these variant pathways, an ANN model was built, consisting of an input layer, two hidden layers, and an output layer, corresponding to 15, 8, 5, and 1 neuron, respectively. Survival analysis showed that this model could effectively distinguish the samples with different risks. Analysis of microarray dataset GSE34289 showed that the accuracy of this model for predicating low-risk and high-risk samples was 77.5 and 86.0%, respectively.\nCONCLUSIONS: This study suggests that the ANN model based on variant pathways can be used for effectively evaluating the risk of thyroid cancer.", "claims": [{"id": "claim-method", "statement": "The DEGs between high-risk samples and low-risk samples were then identified using the limma package (version 3.10.3, http://www.bioconductor.org/packages/2.9/bioc/html/limma.html) [21].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31138213", "locator": "sections[5] \"Data normalization and identification of DEGs\" paragraph 2", "quote": "The DEGs between high-risk samples and low-risk samples were then identified using the limma package (version 3.10.3, http://www.bioconductor.org/packages/2.9/bioc/html/limma.html) [21]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The microarray data GSE34289 was downloaded from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31138213", "locator": "sections[24] \"notes\" paragraph 1", "quote": "The microarray data GSE34289 was downloaded from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:31138213"], "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:GSE34289"], "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:GSE34289"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:31138213", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12881-019-0829-4", "sha256": "sha256:a5cd0d3d09d0327a9fecfe60b62bcb2a46ae22935b5a6019ecc2513881fc8fe0", "bytes": 25499, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12881-019-0829-4", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC6537382", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE34289", "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=GSE34289", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE34289", "version": null, "note": "The microarray data GSE34289 was downloaded from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The microarray data GSE34289 was downloaded from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi).", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM846410", "GSM846411", "GSM846412", "GSM846413", "GSM846414", "GSM846415", "GSM846416", "GSM846417", "GSM846418", "GSM846419", "GSM846420", "GSM846421", "GSM846422", "GSM846423", "GSM846424", "GSM846425", "GSM846426", "GSM846427", "GSM846428", "GSM846429", "GSM846430", "GSM846431", "GSM846432", "GSM846433", "GSM846434", "GSM846435", "GSM846436", "GSM846437", "GSM846438", "GSM846439", "GSM846440", "GSM846441", "GSM846442", "GSM846443", "GSM846444", "GSM846445", "GSM846446", "GSM846447", "GSM846448", "GSM846449", "GSM846450", "GSM846451", "GSM846452", "GSM846453", "GSM846454", "GSM846455", "GSM846456", "GSM846457", "GSM846458", "GSM846459", "GSM846460", "GSM846461", "GSM846462", "GSM846463", "GSM846464", "GSM846465", "GSM846466", "GSM846467", "GSM846468", "GSM846469", "GSM846470", "GSM846471", "GSM846472", "GSM846473", "GSM846474", "GSM846475", "GSM846476", "GSM846477", "GSM846478", "GSM846479", "GSM846480", "GSM846481", "GSM846482", "GSM846483", "GSM846484", "GSM846485", "GSM846486", "GSM846487", "GSM846488", "GSM846489", "GSM846490", "GSM846491", "GSM846492", "GSM846493", "GSM846494", "GSM846495", "GSM846496", "GSM846497", "GSM846498", "GSM846499", "GSM846500", "GSM846501", "GSM846502", "GSM846503", "GSM846504", "GSM846505", "GSM846506", "GSM846507", "GSM846508", "GSM846509", "GSM846510", "GSM846511", "GSM846512", "GSM846513", "GSM846514", "GSM846515", "GSM846516", "GSM846517", "GSM846518", "GSM846519", "GSM846520", "GSM846521", "GSM846522", "GSM846523", "GSM846524", "GSM846525", "GSM846526", "GSM846527", "GSM846528", "GSM846529", "GSM846530", "GSM846531", "GSM846532", "GSM846533", "GSM846534", "GSM846535", "GSM846536", "GSM846537", "GSM846538", "GSM846539", "GSM846540", "GSM846541", "GSM846542", "GSM846543", "GSM846544", "GSM846545", "GSM846546", "GSM846547", "GSM846548", "GSM846549", "GSM846550", "GSM846551", "GSM846552", "GSM846553", "GSM846554", "GSM846555", "GSM846556", "GSM846557", "GSM846558", "GSM846559", "GSM846560", "GSM846561", "GSM846562", "GSM846563", "GSM846564", "GSM846565", "GSM846567", "GSM846568", "GSM846569", "GSM846570", "GSM846571", "GSM846572", "GSM846573", "GSM846574", "GSM846575", "GSM846576", "GSM846577", "GSM846578", "GSM846579", "GSM846580", "GSM846581", "GSM846582", "GSM846583", "GSM846584", "GSM846585", "GSM846586", "GSM846587", "GSM846588", "GSM846589", "GSM846590", "GSM846591", "GSM846592", "GSM846593", "GSM846594", "GSM846595", "GSM846596", "GSM846597", "GSM846598", "GSM846599", "GSM846600", "GSM846601", "GSM846602", "GSM846603", "GSM846604", "GSM846605", "GSM846606", "GSM846607", "GSM846608", "GSM846609", "GSM846610", "GSM846611", "GSM846612", "GSM846613", "GSM846614", "GSM846615", "GSM846616", "GSM846617", "GSM846618", "GSM846619", "GSM846620", "GSM846621", "GSM846622", "GSM846623", "GSM846624", "GSM846625", "GSM846626", "GSM846627", "GSM846628", "GSM846629", "GSM846630", "GSM846631", "GSM846632", "GSM846633", "GSM846634", "GSM846635", "GSM846636", "GSM846637", "GSM846638", "GSM846639", "GSM846640", "GSM846641", "GSM846642", "GSM846643", "GSM846644", "GSM846645", "GSM846646", "GSM846647", "GSM846648", "GSM846649", "GSM846650", "GSM846651", "GSM846652", "GSM846653", "GSM846654", "GSM846655", "GSM846656", "GSM846657", "GSM846658", "GSM846659", "GSM846660", "GSM846661", "GSM846662", "GSM846663", "GSM846664", "GSM846665", "GSM846666", "GSM846667", "GSM846668", "GSM846669", "GSM846670", "GSM846671", "GSM846672", "GSM846673", "GSM846674", "GSM846675", "GSM846676", "GSM846677", "GSM846678", "GSM846679", "GSM846680", "GSM846681", "GSM846682", "GSM846683", "GSM846684", "GSM846685", "GSM846686", "GSM846687", "GSM846688", "GSM846689", "GSM846690", "GSM846691", "GSM846692", "GSM846693", "GSM846694", "GSM846695", "GSM846696", "GSM846697", "GSM846698", "GSM846699", "GSM846700", "GSM846701", "GSM846702", "GSM846703", "GSM846704", "GSM846705", "GSM846706", "GSM846707", "GSM846708", "GSM846709", "GSM846710", "GSM846711", "GSM846712", "GSM846713", "GSM846714", "GSM846715", "GSM846716", "GSM846717", "GSM846718", "GSM846719", "GSM846720", "GSM846721", "GSM846722", "GSM846723", "GSM846724", "GSM846725", "GSM846726", "GSM846727", "GSM846728", "GSM846729", "GSM846730", "GSM846731", "GSM846732", "GSM846733", "GSM846734", "GSM846735", "GSM846736", "GSM846737", "GSM846738", "GSM846739", "GSM846740", "GSM846741", "GSM846742", "GSM846743", "GSM846744", "GSM846745", "GSM846746", "GSM846747", "GSM846748", "GSM846749", "GSM846750", "GSM846751", "GSM846752", "GSM846753", "GSM846754", "GSM846755", "GSM846756", "GSM846757", "GSM846758", "GSM846759", "GSM846760", "GSM846761", "GSM846762", "GSM846763", "GSM846764", "GSM846765", "GSM846766", "GSM846767", "GSM846768", "GSM846769", "GSM846770", "GSM846771", "GSM846772", "GSM846773", "GSM846774", "GSM846775", "GSM846776", "GSM846777"], "sample_count": 367, "group_sizes": null, "group_sizes_basis": null, "platform": "5175;14961", "taxon": "Homo sapiens", "title": "Preoperative Diagnosis of Benign Thyroid Nodules with Indeterminate Cytology", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:31138213:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:88a434947eaf9b0620f94479be89b903b652e3afa0347bf8d35629f643763ee9", "bytes": 2724, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[13]/table-wrap[1]#Tab1", "version": null, "note": "KEGG pathway enrichment analysis for differentially expressed genes", "structure": {"pmcid": "PMC6537382", "section_index": 13, "section_title": "Variant pathway analysis and establishment of ANN model for risk assessment", "row_count": 22, "column_count": 5}, "table": {"label": "Table 1", "caption": "KEGG pathway enrichment analysis for differentially expressed genes", "rows": [["Term", "Enrichment score", "Count", "P value", "Genes"], ["Graft-versus-host disease", "23.93073593", "8", "2.52E-08", "CD86, CD80, HLA-DRB5, FAS, HLA-E, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Allograft rejection", "21.34362934", "8", "5.89E-08", "CD86, CD80, HLA-DRB5, FAS, HLA-E, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Type I diabetes mellitus", "18.80272109", "8", "1.48E-07", "CD86, CD80, HLA-DRB5, FAS, HLA-E, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Autoimmune thyroid disease", "15.18681319", "8", "6.80E-07", "CD86, CD80, HLA-DRB5, FAS, HLA-E, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Viral myocarditis", "13.85463659", "8", "1.29E-06", "CD86, CD80, CASP8, HLA-DRB5, HLA-E, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Herpes simplex infection", "6.473067916", "12", "1.59E-06", "DDX58, HMGN1, IFIH1, GTF2IRD1, CASP8, HLA-DRB5, JAK2, FAS, HLA-E, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Tuberculosis", "5.577078289", "10", "5.85E-05", "FCGR1A, CASP8, HLA-DRB5, FCER1G, ATP6V1H, JAK2, CLEC7A, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Cell adhesion molecules (CAMs)", "6.256539235", "9", "7.58E-05", "CLDN16, CD86, CD80, HLA-DRB5, L1CAM, HLA-E, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Intestinal immune network for IgA production", "12.60182371", "6", "9.50E-05", "CD86, CD80, HLA-DRB5, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Phagosome", "5.806722689", "9", "1.28E-04", "FCGR1A, HLA-DRB5, ITGB5, ATP6V1H, CLEC7A, HLA-E, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Asthma", "16.45238095", "5", "2.05E-04", "HLA-DRB5, FCER1G, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Rheumatoid arthritis", "7.852272727", "7", "2.26E-04", "CD86, CD80, HLA-DRB5, ATP6V1H, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Influenza A", "5.10591133", "9", "3.11E-04", "DDX58, IFIH1, HLA-DRB5, JAK2, CPSF4, FAS, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Systemic lupus erythematosus", "5.893390192", "8", "3.50E-04", "HIST1H2AC, CD86, CD80, FCGR1A, HLA-DRB5, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Leishmaniasis", "8.342052314", "6", "6.70E-04", "FCGR1A, HLA-DRB5, JAK2, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Antigen processing and presentation", "7.793233083", "6", "9.15E-04", "KLRC4, HLA-DRB5, HLA-E, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Toxoplasmosis", "5.855932203", "7", "0.001089", "CASP8, HLA-DRB5, JAK2, BIRC3, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Staphylococcus aureus infection", "9.14021164", "5", "0.001978", "FCGR1A, HLA-DRB5, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Inflammatory bowel disease (IBD)", "7.712053571", "5", "0.003688", "IL18RAP, HLA-DRB5, HLA-DMA, HLA-DQA1, HLA-DRA"], ["HTLV-I infection", "2.69921875", "7", "0.04181", "IL2RB, HLA-DRB5, HLA-E, HLA-DMA, HLA-DQA1, HLA-DRA, APC"], ["Measles", "3.711063373", "5", "0.043409", "DDX58, IL2RB, IFIH1, JAK2, FAS"]], "row_count": 22, "column_count": 5, "numeric_cells": 76, "header_rows": 1, "locator": "section[13]/table-wrap[1]#Tab1"}}, {"id": "asset:table:pmid:31138213:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:c496cecb91ad4db5247d9118cd499c8f56b53b9e494a6063cf941e388d084a1e", "bytes": 1230, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[13]/table-wrap[2]#Tab2", "version": null, "note": "Selection of risk-related pathways", "structure": {"pmcid": "PMC6537382", "section_index": 13, "section_title": "Variant pathway analysis and establishment of ANN model for risk assessment", "row_count": 11, "column_count": 3}, "table": {"label": "Table 2", "caption": "Selection of risk-related pathways", "rows": [["Pathway", "P value_", "Genes"], ["Measles", "2.03E-29", "DDX58, IL2RB, IFIH1, JAK2, FAS"], ["Antigen processing and presentation", "7.42E-19", "KLRC4, HLA-DRB5, HLA-E, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Rheumatoid arthritis", "1.70E-13", "CD86, CD80, HLA-DRB5, ATP6V1H, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Phagosome", "5.84E-12", "FCGR1A, HLA-DRB5, ITGB5, ATP6V1H, CLEC7A, HLA-E, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Systemic lupus erythematosus", "1.31E-11", "HIST1H2AC, CD86, CD80, FCGR1A, HLA-DRB5, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Herpes simplex infection", "1.18E-06", "DDX58, HMGN1, IFIH1, GTF2IRD1, CASP8, HLA-DRB5, JAK2, FAS, HLA-E, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Inflammatory bowel disease (IBD)", "1.14E-05", "IL18RAP, HLA-DRB5, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Tuberculosis", "0.000357276", "FCGR1A, CASP8, HLA-DRB5, FCER1G, ATP6V1H, JAK2, CLEC7A, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Type I diabetes mellitus", "0.001284502", "CD86, CD80, HLA-DRB5, FAS, HLA-E, HLA-DMA, HLA-DQA1, HLA-DRA"], ["Toxoplasmosis", "0.001643", "CASP8, HLA-DRB5, JAK2, BIRC3, HLA-DMA, HLA-DQA1, HLA-DRA"]], "row_count": 11, "column_count": 3, "numeric_cells": 16, "header_rows": 1, "locator": "section[13]/table-wrap[2]#Tab2"}}], "gaps": ["asset:data:geo:GSE34289 not downloaded", "asset:data:geo:GSE34289 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "limma_voom", "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": 1.0, "band": "verbatim", "quote": "The DEGs between high-risk samples and low-risk samples were then identified using the limma package (version 3.10.3, http://www.bioconductor.org/packages/2.9/bioc/html/limma.html) [21]."}}, {"id": "method-2", "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": 0.7, "band": "medium", "quote": "pathway enrichment"}}], "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": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "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": ["GSE34289"], "resolved_accessions": ["GSE34289"], "statements": ["The microarray data GSE34289 was downloaded from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi)."], "basis": "The paper names GSE34289 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": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:31138213", "data:geo:GSE34289", "asset:table:pmid:31138213:1", "asset:table:pmid:31138213:2"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE34289"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:14:48Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 3, "usage": {"prompt_tokens": 20371, "completion_tokens": 1811, "cached_tokens": 784}}, "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:31138213", "type": "paper", "label": "pmid:31138213"}, {"id": "source:pmid:31138213", "type": "manuscript", "label": "PMID 31138213 full text"}, {"id": "data:geo:GSE34289", "type": "dataset", "label": "GEO GSE34289"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:31138213", "type": "paper", "label": "pmid:31138213"}, {"id": "source:pmid:31138213", "type": "manuscript", "label": "PMID 31138213 full text"}, {"id": "data:geo:GSE34289", "type": "dataset", "label": "GEO GSE34289"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-31138213", "type": "extraction", "used": ["source:pmid:31138213"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE34289", "type": "accession_resolution", "used": ["data:geo:GSE34289"], "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:31138213", "parent_hash": "sha256:e687381160fe17602c9fc318a81d308372e6454fa015198bea1b6dec3a919614", "fork_of": null, "generation": 7}, "gaps": ["asset:data:geo:GSE34289 licence not read", "asset:data:geo:GSE34289 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["ict the risk of thyroid cancer. METHODS: The RNASeq data of 482 thyroid cancer samples were down"], "order_basis": "paper_text_order:236", "id": "assay:1"}, {"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ival analysis and analysis of an independent microarray dataset (GSE34289) for thyroid cancer. RESUL", "he samples with different risks. Analysis of microarray dataset GSE34289 showed that the accuracy of"], "order_basis": "paper_text_order:781", "id": "assay:2"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The DEGs between high-risk samples and low-risk samples were then identified using the limma package (version 3.10.3, http://www.bioconductor.org/packages/2.9/bioc/html/limma.html) [21]."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}