{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:20677550", "kind": "science-record", "revision": 6, "content_hash": "sha256:583299e2a0212ccb22761b39ddab412836cde17d0f3a1beecf1d5620abaa23dd", "created_at": "2026-11-01T15:14:34Z", "updated_at": "2026-11-01T21:19:36Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "[Identification of candidate genes for lung adenocarcinoma using Toppgene].", "doi": "10.3779/j.issn.1009-3419.2010.04.02", "pmid": "20677550", "authors": ["Guiping Wang", "Yun Ye", "Wenling Zheng", "Wenli Ma"], "journal": "Zhongguo fei ai za zhi = Chinese journal of lung cancer", "year": 2010, "abstract": "BACKGROUND AND OBJECTIVE: Lung adenocarcinoma (AC) is the most common type of lung cancer, however, its mechanism of oncongenesis is still unknown. The aim of this study is to screen candidate genes of lung adenocarcinoma using bioinformatics strategy and elucidate the mechanism of lung adenocarcinoma.\nMETHODS: Two published microarray data (GSE7670 and GSE10072) was obtained from Gene Expression Omnibus (GEO). Significance analysis of microarrays was performed with the software dchip, and differential expression genes from dchip analysis were defined as \"test gene set\". Genes correlated with lung adenocarcinoma, obtained by data mining tools genecard and Fable were regarded as \"train gene set\". Finally, candidate genes of lung adenocarcinoma were screened by the tool \"Toppgene\".\nRESULTS: Three hundred and forty-four differential genes were defined as \"test gene set\", and 277 genes correlated with lung adenocarcinoma were regarded as \"train gene set\". Thirty-six candidate genes were screened out by Toppgene, among them, 21 genes had nearly no report in cancer. In the following QRT-PCR experiment, CD36, PMAIP1 and FABP4 were down-regulated expression in A549, which coincided with the gene chip.\nCONCLUSION: It is demonstrated that Toppgene is useful in identification of the candidate genes of lung adenocacinoma, which provides the proof for the discovery of the specific disease genes.", "claims": [{"id": "claim-method", "statement": "我们对GSE10072和GSE7670数据集中质量合格芯片样本分别采用dchip进行差异基因分析，具体操作方法按dchip操作指南进行（http://www.dchip.org），2-fold change的基因被选择为差异表达基因。最后，采用交集方法获得共同差异基因。", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:20677550", "locator": "sections[7] \"肺腺癌差异表达基因分析[9]\" paragraph 2", "quote": "我们对GSE10072和GSE7670数据集中质量合格芯片样本分别采用dchip进行差异基因分析，具体操作方法按dchip操作指南进行（http://www.dchip.org），2-fold change的基因被选择为差异表达基因。最后，采用交集方法获得共同差异基因。"}], "state": "complete"}, {"id": "claim-data-access", "statement": "首先，我们从NCBI的GEO数据库（http:www.ncbi.nlm.nih.gov/geo）中下载2个基因表达谱数据集，即GSE7670和GSE10072。其中，GSE7670数据集来源于台湾台北荣民总医院（Taipei veterans general hospital），采用GPL96芯片平台（[HG-U133A] Affymetrix Human Genome U133A Array），包括27个配对的正常肺组织与肺腺癌组织、2个混合组织、2个商业化的正常肺组织、1个正常肺上皮细胞株与7个商业化肺癌细胞株，共64个样本；而另一个数据集GSE10072则来源于美国N.I.H遗传流行病学部（Genetic Epidemiology Branch），也采用GPL96芯片平台，疾病组织类型为肺腺癌，包括58个腺癌和49个正常肺组织，共107个样本。", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:20677550", "locator": "sections[6] \"获取GEO数据集\" paragraph 2", "quote": "首先，我们从NCBI的GEO数据库（http:www.ncbi.nlm.nih.gov/geo）中下载2个基因表达谱数据集，即GSE7670和GSE10072。其中，GSE7670数据集来源于台湾台北荣民总医院（Taipei veterans general hospital），采用GPL96芯片平台（[HG-U133A] Affymetrix Human Genome U133A Array），包括27个配对的正常肺组织与肺腺癌组织、2个混合组织、2个商业化的正常肺组织、1个正常肺上皮细胞株与7个商业化肺癌细胞株，共64个样本；而另一个数据集GSE10072则来源于美国N.I.H遗传流行病学部（Genetic Epidemiology Branch），也采用GPL96芯片平台，疾病组织类型为肺腺癌，包括58个腺癌和49个正常肺组织，共107个样本。"}], "state": "complete"}, {"id": "claim-target-result", "statement": "该研究从GEO数据库获取GSE10072和GSE7670数据集，经dchip差异表达分析形成检测基因集，并将Genecards与Fable挖掘的已知疾病基因作为训练基因集，利用Toppgene筛选出36个候选疾病基因，其中21个在肿瘤方面的研究几无报道。", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:20677550", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "从GEO数据库中获得GSE10072和GSE7670两个数据集，然后利用dchip软件进行差异表达基因分析，将其获得的差异基因定义为“检测基因集”（test gene set）；采用genecard和Fable文献挖掘已知肺腺癌疾病基因，并将其定义为“训练基因集”（train gene set）；最后，利用Toppgene筛选肺腺癌候选基因，并通过荧光定量PCR对其获得的部分基因进行验证。"}, {"asset": "source:pmid:20677550", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "采用Toppgene共获得36个候选疾病基因，其中21个基因则在肿瘤方面的研究几无报道。"}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "该研究从GEO数据库获取GSE10072和GSE7670数据集，经dchip差异表达分析形成检测基因集，并将Genecards与Fable挖掘的已知疾病基因作为训练基因集，利用Toppgene筛选出36个候选疾病基因，其中21个在肿瘤方面的研究几无报道。", "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:20677550"], "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:GSE10072"], "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:GSE10072"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:20677550", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3779/j.issn.1009-3419.2010.04.02", "sha256": 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"首先，我们从NCBI的GEO数据库（http:www.ncbi.nlm.nih.gov/geo）中下载2个基因表达谱数据集，即GSE7670和GSE10072。其中，GSE7670数据集来源于台湾台北荣民总医院（Taipei veterans general hospital），采用GPL96芯片平台（[HG-U133A] Affymetrix Human Genome U133A Array），包括27个配对的正常肺组织与肺腺癌组织、2个混合组织、2个商业化的正常肺组织、1个正常肺上皮细胞株与7个商业化肺癌细胞株，共64个样本；而另一个数据集GSE10072则来源于美国N.I.H遗传流行病学部（Genetic Epidemiology Branch），也采用GPL96芯片平台，疾病组织类型为肺腺癌，包括58个腺癌和49个正常肺组织，共107个样本。", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "首先，我们从NCBI的GEO数据库（http:www.ncbi.nlm.nih.gov/geo）中下载2个基因表达谱数据集，即GSE7670和GSE10072。其中，GSE7670数据集来源于台湾台北荣民总医院（Taipei veterans general hospital），采用GPL96芯片平台（[HG-U133A] Affymetrix Human Genome U133A Array），包括27个配对的正常肺组织与肺腺癌组织、2个混合组织、2个商业化的正常肺组织、1个正常肺上皮细胞株与7个商业化肺癌细胞株，共64个样本；而另一个数据集GSE10072则来源于美国N.I.H遗传流行病学部（Genetic Epidemiology Branch），也采用GPL96芯片平台，疾病组织类型为肺腺癌，包括58个腺癌和49个正常肺组织，共107个样本。", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM254625", "GSM254626", "GSM254627", "GSM254628", "GSM254629", "GSM254630", "GSM254631", "GSM254632", "GSM254633", "GSM254634", "GSM254635", "GSM254636", "GSM254637", "GSM254638", "GSM254639", "GSM254640", "GSM254641", "GSM254642", "GSM254643", "GSM254644", "GSM254645", "GSM254646", "GSM254647", "GSM254648", "GSM254649", "GSM254650", "GSM254651", "GSM254652", "GSM254653", "GSM254654", "GSM254655", "GSM254656", "GSM254657", "GSM254658", "GSM254659", "GSM254660", "GSM254661", "GSM254662", "GSM254663", "GSM254664", "GSM254665", "GSM254666", "GSM254667", "GSM254668", "GSM254669", "GSM254670", "GSM254671", "GSM254672", "GSM254673", "GSM254674", "GSM254675", "GSM254676", "GSM254677", "GSM254678", "GSM254679", "GSM254680", "GSM254681", "GSM254682", "GSM254683", "GSM254684", "GSM254685", "GSM254686", "GSM254687", "GSM254688", "GSM254689", "GSM254690", "GSM254691", "GSM254692", "GSM254693", "GSM254694", "GSM254695", "GSM254696", "GSM254697", "GSM254698", "GSM254699", "GSM254700", "GSM254701", "GSM254702", "GSM254703", "GSM254704", "GSM254705", "GSM254706", "GSM254707", "GSM254708", "GSM254709", "GSM254710", "GSM254711", "GSM254712", "GSM254713", "GSM254714", "GSM254715", "GSM254716", "GSM254717", "GSM254718", "GSM254719", "GSM254720", "GSM254721", "GSM254722", "GSM254723", "GSM254724", "GSM254725", "GSM254726", "GSM254727", "GSM254728", "GSM254729", "GSM254730", "GSM254731"], "sample_count": 107, "group_sizes": null, "group_sizes_basis": null, "platform": "96", "taxon": "Homo sapiens", "title": "Gene expression signature of cigarette smoking and its role in lung adenocarcinoma development and survival", "resolution_checked_at": "2026-11-01T15:30:21Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE7670", "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=GSE7670", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE7670", "version": null, "note": "首先，我们从NCBI的GEO数据库（http:www.ncbi.nlm.nih.gov/geo）中下载2个基因表达谱数据集，即GSE7670和GSE10072。其中，GSE7670数据集来源于台湾台北荣民总医院（Taipei veterans general hospital），采用GPL96芯片平台（[HG-U133A] Affymetrix Human Genome U133A Array），包括27个配对的正常肺组织与肺腺癌组织、2个混合组织、2个商业化的正常肺组织、1个正常肺上皮细胞株与7个商业化肺癌细胞株，共64个样本；而另一个数据集GSE10072则来源于美国N.I.H遗传流行病学部（Genetic Epidemiology Branch），也采用GPL96芯片平台，疾病组织类型为肺腺癌，包括58个腺癌和49个正常肺组织，共107个样本。", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "首先，我们从NCBI的GEO数据库（http:www.ncbi.nlm.nih.gov/geo）中下载2个基因表达谱数据集，即GSE7670和GSE10072。其中，GSE7670数据集来源于台湾台北荣民总医院（Taipei veterans general hospital），采用GPL96芯片平台（[HG-U133A] Affymetrix Human Genome U133A Array），包括27个配对的正常肺组织与肺腺癌组织、2个混合组织、2个商业化的正常肺组织、1个正常肺上皮细胞株与7个商业化肺癌细胞株，共64个样本；而另一个数据集GSE10072则来源于美国N.I.H遗传流行病学部（Genetic Epidemiology Branch），也采用GPL96芯片平台，疾病组织类型为肺腺癌，包括58个腺癌和49个正常肺组织，共107个样本。", 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null, "platform": "96", "taxon": "Homo sapiens", "title": "Expression data from Lung cancer", "resolution_checked_at": "2026-11-01T15:14:33Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:20677550:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:7904443232ba033d06e9ffb63d737317b11d3c8cd7d5fb3d2219529900d2b982", "bytes": 488, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[13]/table-wrap[1]#Table1", "version": null, "note": "GSE7670和GSE10072中芯片样本差异表达基因分析结果Analysis of lung adenocarcinoma differential expression genes against two GEO gene sets GSE10072 and GSE7670", "structure": {"pmcid": "PMC6000438", "section_index": 13, "section_title": "肺腺癌差异表达基因", "row_count": 4, "column_count": 4}, "table": {"label": "1", "caption": "GSE7670和GSE10072中芯片样本差异表达基因分析结果Analysis of lung adenocarcinoma differential expression genes against two GEO gene sets GSE10072 and GSE7670", "rows": [["GEO datasets", "Platform", "Up-expressed gene", "Down-expressed gene"], ["GSE7670", "GPL96", "123", "385"], ["GSE10072", "GPL96", "198", "363"], ["Co-expressed gene", "", "94", "285"]], "row_count": 4, "column_count": 4, "numeric_cells": 10, "header_rows": 1, "locator": "section[13]/table-wrap[1]#Table1"}}, {"id": "asset:table:pmid:20677550:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:4e76db5ca4678f1d5db1f869eae800bd6435be5239995d04e77a7ed1504340a8", "bytes": 2161, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[15]/table-wrap[1]#Table2", "version": null, "note": "Toppgene筛选新的肺腺癌疾病候选基因（注：选取P < 0.01的基因）The screen of lung adenocarcinoma candidate genes using Toppgene (Note: Genes were selected based on P < 0.01)", "structure": {"pmcid": "PMC6000438", "section_index": 15, "section_title": "筛选新的肺腺癌疾病基因", "row_count": 37, "column_count": 5}, "table": {"label": "2", "caption": "Toppgene筛选新的肺腺癌疾病候选基因（注：选取P < 0.01的基因）The screen of lung adenocarcinoma candidate genes using Toppgene (Note: Genes were selected based on P < 0.01)", "rows": [["Rank", "Gene Symbol", "Gene ID", "Average score", "P"], ["1", "CD36", "948", "0.470 761 5", "0.000 000 1"], ["2", "HBEGF", "1839", "0.529 077 5", "0.000 000 6"], ["3", "PMAIP1", "5366", "0.572 612 2", "0.000 001 1"], ["4", "TYMS", "7298", "0.485 545 3", "0.000 001 8"], ["5", "TEK", "7010", "0.486 797 7", "0.000 001 8"], ["6", "COL1A1", "1277", "0.319 382 1", "0.000 004"], ["7", "IGFBP3", "3486", "0.456 963 2", "0.000 006 9"], ["8", "SPP1", "6696", "0.503 422 5", "0.000 007"], ["9", "EDN1", "1906", "0.471 195 9", "0.000 008 1"], ["10", "TIE1", "7075", "0.541 537 4", "0.000 010 4"], ["11", "TGFBR3", "7049", "0.497 567 5", "0.000 010 4"], ["12", "CDKN1C", "1028", "0.431 009 4", "0.000 013 1"], ["13", "NR4A1", "3164", "0.401 529 2", "0.000 017 5"], ["14", "CXCL2", "2920", "0.455 321 7", "0.000 030 6"], ["15", "BMP2", "650", "0.380 468 4", "0.000 039 1"], ["16", "CSF3", "1440", "0.438 977 1", "0.000 200 2"], ["17", "SFN", "2810", "0.455 187 2", "0.000 266 3"], ["18", "MMP7", "4316", "0.398 214 1", "0.000 267"], ["19", "COL1A2", "1278", "0.362 644 5", "0.000 572 2"], ["20", "FABP4", "2167", "0.330 210 4", "0.000 708 5"], ["21", "CEACAM1", "634", "0.404 989 1", "0.000 729 4"], ["22", "LEPR", "3953", "0.370 081 7", "0.001 032 8"], ["23", "DST", "667", "0.388 865 5", "0.001 492 4"], ["24", "UBE2C", "11065", "0.345 610 4", "0.001 553 9"], ["25", "GATA6", "2627", "0.280 920 4", "0.001 912 6"], ["26", "ATF3", "467", "0.307 962 8", "0.002 073 1"], ["27", "SORBS1", "10580", "0.395 258 5", "0.002 167 8"], ["28", "CXCL3", "2921", "0.384 477 2", "0.002 625 5"], ["29", "CRYAB", "1410", "0.352 635 4", "0.002 788 1"], ["30", "EDNRB", "1910", "0.334 035 3", "0.003 291 3"], ["31", "DLC1", "10395", "0.407 277 2", "0.003 520 2"], ["32", "HBB", "3043", "0.283 212 9", "0.004 263 6"], ["33", "CP", "1356", "0.349 502 5", "0.004 849 8"], ["34", "COL3A1", "1281", "0.291 960 6", "0.006 152 1"], ["35", "SLC2A1", "6513", "0.263 899 8", "0.006 28"], ["36", "NME1", "4830", "0.338 435 6", "0.010 138 1"]], "row_count": 37, "column_count": 5, "numeric_cells": 145, "header_rows": 1, "locator": "section[15]/table-wrap[1]#Table2"}}, {"id": "asset:table:pmid:20677550:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:dc52b4566c53c2ab48491e25bc6508b5dbdcbb3dd0f5f7c0e9b4f8e143c041f0", "bytes": 912, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[16]/table-wrap[1]#Table3", "version": null, "note": "CD36、PMAIP1及FABP4的荧光定量PCR实验结果Expression of three genes CD36, PMAIP1 and FABP4 using fluorescent quantitation PCR", "structure": {"pmcid": "PMC6000438", "section_index": 16, "section_title": "荧光定量PCR实验验证", "row_count": 10, "column_count": 6}, "table": {"label": "3", "caption": "CD36、PMAIP1及FABP4的荧光定量PCR实验结果Expression of three genes CD36, PMAIP1 and FABP4 using fluorescent quantitation PCR", "rows": [["Gene", "Sample", "Average Ct", "Average△CT", "Average △△CT", "2-△△Ct"], ["△Ct=target gene Ct-actin Ct; △△Ct=sample target gene△Ct-reference sample target gene△Ct; when the amplification rate of PCR get close to 100%, relative sample template product=2-△△Ct."], ["CD36", "16-HBE", "31.41", "13.43", "0", "1"], ["CD36", "A549", "32.21", "13.73", "0.285", "0.821"], ["PMAIP1", "16-HBE", "34.34", "16.36", "0", "1"], ["PMAIP1", "A549", "40.96", "22.48", "7.12", "0.0072"], ["FABP4", "16-HBE", "31.24", "13.26", "0", "1"], ["FABP4", "A549", "32.51", "14.03", "0.77", "0.588"], ["β-actin", "16-HBE", "17.98", "", "", ""], ["β-actin", "A549", "18.48", "", "", ""]], "row_count": 10, "column_count": 6, "numeric_cells": 38, "header_rows": 1, "locator": "section[16]/table-wrap[1]#Table3"}}], "gaps": ["asset:data:geo:GSE10072 not downloaded", "asset:data:geo:GSE10072 licence not read", "asset:data:geo:GSE7670 not downloaded", "asset:data:geo:GSE7670 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": null, "specific": null, "label": "dchip软件差异表达基因分析，采用2-fold change筛选并以交集法获得共同差异基因", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "我们对GSE10072和GSE7670数据集中质量合格芯片样本分别采用dchip进行差异基因分析，具体操作方法按dchip操作指南进行（http://www.dchip.org），2-fold change的基因被选择为差异表达基因。最后，采用交集方法获得共同差异基因。"}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "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": "blocked", "tier": "R4", "blocking_axis": "method", "blocked_on": "method:not_determinable", "axes": {"method": {"tier": "R4", "expressible": false, "required_operations": [], "missing_operations": [], "basis": "The reader quoted the method the paper names (dchip软件差异表达基因分析，采用2-fold change筛选并以交集法获得共同差异基因), but the corpus's method extractor could not map it onto a DSL operation, so the method is published but not expressible."}, "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": ["GSE7670", "GSE10072"], "resolved_accessions": ["GSE7670", "GSE10072"], "statements": ["首先，我们从NCBI的GEO数据库（http:www.ncbi.nlm.nih.gov/geo）中下载2个基因表达谱数据集，即GSE7670和GSE10072。其中，GSE7670数据集来源于台湾台北荣民总医院（Taipei veterans general hospital），采用GPL96芯片平台（[HG-U133A] Affymetrix Human Genome U133A Array），包括27个配对的正常肺组织与肺腺癌组织、2个混合组织、2个商业化的正常肺组织、1个正常肺上皮细胞株与7个商业化肺癌细胞株，共64个样本；而另一个数据集GSE10072则来源于美国N.I.H遗传流行病学部（Genetic Epidemiology Branch），也采用GPL96芯片平台，疾病组织类型为肺腺癌，包括58个腺癌和49个正常肺组织，共107个样本。"], "basis": "The paper names GSE7670, GSE10072 in NCBI GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:20677550", "data:geo:GSE10072", "asset:table:pmid:20677550:1", "asset:table:pmid:20677550:2", "asset:table:pmid:20677550:3"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE10072"]}, "gaps": ["method:not_determinable"]}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:20:45Z", "independence": "same_provider"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 8, "usage": {"prompt_tokens": 30616, "completion_tokens": 5500, "cached_tokens": 23532}}, "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:20677550", "type": "paper", "label": "pmid:20677550"}, {"id": "source:pmid:20677550", "type": "manuscript", "label": "PMID 20677550 full text"}, {"id": "data:geo:GSE10072", "type": "dataset", "label": "GEO GSE10072"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:20677550", "type": "paper", "label": "pmid:20677550"}, {"id": "source:pmid:20677550", "type": "manuscript", "label": "PMID 20677550 full text"}, {"id": "data:geo:GSE10072", "type": "dataset", "label": "GEO GSE10072"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-20677550", "type": "extraction", "used": ["source:pmid:20677550"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE10072", "type": "accession_resolution", "used": ["data:geo:GSE10072"], "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:20677550", "parent_hash": "sha256:69aba93e4f2a77d495f9141a863b6cb51b597ec27742800b81d03eddf454778f", "fork_of": null, "generation": 5}, "gaps": ["asset:data:geo:GSE10072 licence not read", "asset:data:geo:GSE10072 not downloaded", "asset:data:geo:GSE7670 licence not read", "asset:data:geo:GSE7670 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["lung adenocarcinoma. METHODS: Two published microarray data (GSE7670 and GSE10072) was obtained fro"], "order_basis": "paper_text_order:359", "id": "assay:1"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.77, "evidence": ["and FABP4 were down-regulated expression in A549, which coincided with the gene chip. CONCLUS"], "order_basis": "paper_text_order:1203", "id": "assay:2"}]},"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":"2026-11-04T01:45:19+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}}}