{"data":{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40826700", "kind": "science-record", "revision": 2, "content_hash": "sha256:6e65052c7755ca1102f3e53383f1ae8d3b51e40fd9a214f1d9228aaa2f1aae42", "created_at": "2026-11-01T10:25:52Z", "updated_at": "2026-11-01T14:01:46Z", "generator": {"name": "corpus-assay-engine", "converter": "sep_to_sci_v1", "source_package_schema": "urn:bntrg:sep:1.0.0"}, "paper": {"state": "partial", "title": "Identification of biomarkers and potential therapeutic targets of breast cancer using bioinformatics analysis.", "doi": "10.1097/md.0000000000043973", "pmid": "40826700", "authors": null, "journal": "Medicine", "year": 2025, "abstract": null, "claims": [{"id": "claim-1", "statement": "the headline numerical result the paper states for its main finding", "kind": "quantitative", "state": "complete", "target": {"value": 4.0, "unit": "potential biomarkers", "tolerance": null, "source": "chars 4572-4672 of source sha256 f75f271b744a25d8c199261cfabab399c9ce4b7cec3527ec4bebd4617ad0600b"}, "evidence": [{"asset": "source:pmid:40826700", "locator": "chars 4572-4672 of source sha256 f75f271b744a25d8c199261cfabab399c9ce4b7cec3527ec4bebd4617ad0600b", "quote": "Our present study identifies 4 potential biomarkers for BRCA including AURKA, DTL, NUSAP1, and RRM2."}]}], "gaps": ["abstract", "authors"]}, "experiment": {"state": "partial", "objective": "the headline numerical result the paper states for its main finding", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate and its interval from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The number a replication must land on, and the sentence it came from.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:40826700"], "outputs": ["the published estimate, its unit and its interval"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data behind the published result", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:not_downloaded", "description": "The published result cannot be recomputed without the data the paper analysed.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the source data with its provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the analysis programme", "kind": "analysis", "state": "blocked", "blocked_on": "no owned computational capability is bound to this experiment", "description": "Re-run the paper's analysis on the source data and produce the registered result. | SEP input not carried into the asset list: materials:the source data behind the published result in pmid:40826700", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the registered result"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:not_downloaded", "step:run_analysis blocked on no owned computational capability is bound to this experiment", "step:run_analysis input 'materials:the source data behind the published result in pmid:40826700' does not resolve to a declared asset"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40826700", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1097/md.0000000000043973", "sha256": "sha256:f75f271b744a25d8c199261cfabab399c9ce4b7cec3527ec4bebd4617ad0600b", "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1097/md.0000000000043973", "version": null, "note": "Source read by the package builder: full_text.", "structure": {"access_state": "full_text"}}, {"id": "asset:table:pmid:40826700:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:bc47dccc4d454b1a893d407548b2711c4bfd7e0a1ff7cec85fde790cf7d0e6e4", "bytes": 591, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[10]/table-wrap[1]#T1", "version": null, "note": "Primers used for RT-qPCR in this study.", "structure": {"pmcid": "PMC12366978", "section_index": 10, "section_title": "2.8. Hub genes validation by reverse transcription quantitative polymerase chain reaction (RT-qPCR)", "row_count": 7, "column_count": 3}, "table": {"label": "Table 1", "caption": "Primers used for RT-qPCR in this study.", "rows": [["Gene", "Forward primer (5′–3′)", "Reverse primer (5′–3′)"], ["GAPDH", "TGCACCACCAACTGCTTAGC", "GGCATGGACTGTGGTCATGAG"], ["AURKA", "TCTTCCCAGCGCATTCCTTT", "TGGTTGCCTGCAATTGCTTC"], ["DTL", "TCTCCTCCGTCTCTCCCAAG", "GCTTGGGATGACTTCTGGCT"], ["NUSAP1", "GTGTGGACCCTGACTCACAG", "CTTCTTGGTGCTCGTCTGGT"], ["RRM2", "AAGAAGAAGGCAGACTGGGC", "CCAGGCATCAGTCCTCGTTT"], ["FGF2", "GCTGTACTGCAAAAACGGGG", "AGCCAGGTAACGGTTAGCAC"]], "row_count": 7, "column_count": 3, "numeric_cells": 2, "header_rows": 1, "locator": "section[10]/table-wrap[1]#T1"}}, {"id": "asset:table:pmid:40826700:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:0288bfd01f244b2b0bf332f5dc619d65560aa16ed7f53e3d121064c38799f1bb", "bytes": 1006, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[12]/table-wrap[1]#T2", "version": null, "note": "The information of the overlapping differentially expressed genes (DEGs).", "structure": {"pmcid": "PMC12366978", "section_index": 12, "section_title": "3.1. Identification of DEGs", "row_count": 11, "column_count": 11}, "table": {"label": "Table 2", "caption": "The information of the overlapping differentially expressed genes (DEGs).", "rows": [["Category", "Gene symbol"], ["Upregulated DEGs", "COL1A1", "FN1", "POSTN", "BGN", "GPRC5A", "MMP11", "CEACAM6", "COL11A1", "TOP2A", "COL10A1"], ["COMP", "ISG15", "HN1", "SQLE", "INHBA", "PAFAH1B3", "RRM2", "S100P", "BIRC5", "CDK1"], ["NUSAP1", "CDC20", "MMP1", "ASPM", "DTL", "KIF20A", "NEK2", "AURKA", "CEP55", "MELK"], ["HMMR", "SOX11", "CDCA3", "", "", "", "", "", "", ""], ["Downregulated DEGs", "SFRP1", "CD36", "ANXA1", "FABP4", "ADH1B", "CAV1", "FHL1", "LPL", "PLIN1", "CRYAB"], ["FOSB", "SORBS1", "NTRK2", "TGFBR3", "ACACB", "MME", "CFD", "ITIH5", "ENPP2", "CHRDL1"], ["MAOA", "CAV2", "SEMA3G", "LMOD1", "LEP", "TF", "ITM2A", "ITGA7", "DMD", "RBP4"], ["PPP1R1A", "AKR1C3", "CSN1S1", "LDB2", "IL33", "ABCA8", "SPRY2", "PPARG", "FGF2", "S100B"], ["EDNRB", "CHL1", "HLF", "ATP1A2", "TIMP4", "PCK1", "MEOX2", "CXCL2", "MT1M", "TNMD"], ["HSPB2", "", "", "", "", "", "", "", "", ""]], "row_count": 11, "column_count": 11, "numeric_cells": 12, "header_rows": 1, "locator": "section[12]/table-wrap[1]#T2"}}, {"id": "asset:table:pmid:40826700:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:13db5716e375cc8fadee5700dd176e3dd89fc2404f86f342e105cae0b78d9f13", "bytes": 2783, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[13]/table-wrap[1]#T3", "version": null, "note": "Gene ontology analysis of overlapping DEGs in breast cancer.", "structure": {"pmcid": "PMC12366978", "section_index": 13, "section_title": "3.2. Functional enrichment", "row_count": 34, "column_count": 5}, "table": {"label": "Table 3", "caption": "Gene ontology analysis of overlapping DEGs in breast cancer.", "rows": [["GO analysis", "Term", "Gene count", "%", "P value"], ["GOTERM_BP_DIRECT", "GO:0051301~cell division", "7", "28", "5.30E−06"], ["GOTERM_BP_DIRECT", "GO:0090307~mitotic spindle assembly", "4", "16", "2.64E−05"], ["GOTERM_BP_DIRECT", "GO:0000086~G2/M transition of mitotic cell cycle", "4", "16", "3.17E−05"], ["GOTERM_BP_DIRECT", "GO:0000281~mitotic cytokinesis", "4", "16", "8.56E−05"], ["GOTERM_BP_DIRECT", "GO:0042593~glucose homeostasis", "4", "16", "3.48E−04"], ["GOTERM_BP_DIRECT", "GO:0009617~response to bacterium", "4", "16", "3.95E−04"], ["GOTERM_BP_DIRECT", "GO:0010629~negative regulation of gene expression", "5", "20", "4.95E−04"], ["GOTERM_BP_DIRECT", "GO:0000278~mitotic cell cycle", "4", "16", "7.45E−04"], ["GOTERM_BP_DIRECT", "GO:0006468~protein phosphorylation", "5", "20", "0.001019056"], ["GOTERM_BP_DIRECT", "GO:0014823~response to activity", "3", "12", "0.001675663"], ["GOTERM_BP_DIRECT", "GO:0006629~lipid metabolic process", "4", "16", "0.00201127"], ["GOTERM_BP_DIRECT", "GO:0071300~cellular response to retinoic acid", "3", "12", "0.003254841"], ["GOTERM_BP_DIRECT", "GO:0048511~rhythmic process", "3", "12", "0.004124865"], ["GOTERM_CC_DIRECT", "GO:0030496~midbody", "7", "28", "6.54E−08"], ["GOTERM_CC_DIRECT", "GO:0005813~centrosome", "8", "32", "7.35E−06"], ["GOTERM_CC_DIRECT", "GO:0005876~spindle microtubule", "4", "16", "1.60E−05"], ["GOTERM_CC_DIRECT", "GO:0005819~spindle", "5", "20", "2.62E−05"], ["GOTERM_CC_DIRECT", "GO:0072686~mitotic spindle", "4", "16", "6.33E−04"], ["GOTERM_CC_DIRECT", "GO:0000776~kinetochore", "4", "16", "8.98E−04"], ["GOTERM_CC_DIRECT", "GO:0005829~cytosol", "15", "60", "0.001220631"], ["GOTERM_CC_DIRECT", "GO:0005737~cytoplasm", "14", "56", "0.005263969"], ["GOTERM_CC_DIRECT", "GO:0005874~microtubule", "4", "16", "0.005979865"], ["GOTERM_CC_DIRECT", "GO:0005811~lipid droplet", "3", "12", "0.006787893"], ["GOTERM_CC_DIRECT", "GO:0032133~chromosome passenger complex", "2", "8", "0.008016755"], ["GOTERM_CC_DIRECT", "GO:0000922~spindle pole", "3", "12", "0.01210966"], ["GOTERM_CC_DIRECT", "GO:0072687~meiotic spindle", "2", "8", "0.017103345"], ["GOTERM_CC_DIRECT", "GO:0005814~centriole", "3", "12", "0.017624847"], ["GOTERM_CC_DIRECT", "GO:0015630~microtubule cytoskeleton", "3", "12", "0.022337357"], ["GOTERM_MF_DIRECT", "GO:0106310~protein serine kinase activity", "4", "16", "0.010182819"], ["GOTERM_MF_DIRECT", "GO:0004674~protein serine/threonine kinase activity", "4", "16", "0.011432112"], ["GOTERM_MF_DIRECT", "GO:0005524~ATP binding", "6", "24", "0.038167489"], ["GOTERM_MF_DIRECT", "GO:0004672~protein kinase activity", "3", "12", "0.046022875"], ["GOTERM_MF_DIRECT", "GO:0008017~microtubule binding", "3", "12", "0.046022875"]], "row_count": 34, "column_count": 5, "numeric_cells": 132, "header_rows": 1, "locator": "section[13]/table-wrap[1]#T3"}}, {"id": "asset:table:pmid:40826700:4", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:6595dc97000e0282e8c52302df3a014efd06023860daf8813ab334b2e22943df", "bytes": 505, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[13]/table-wrap[2]#T4", "version": null, "note": "KEGG pathway analysis of overlapping DEGs in breast cancer.", "structure": {"pmcid": "PMC12366978", "section_index": 13, "section_title": "3.2. Functional enrichment", "row_count": 5, "column_count": 5}, "table": {"label": "Table 4", "caption": "KEGG pathway analysis of overlapping DEGs in breast cancer.", "rows": [["Category", "Term", "Gene count", "%", "P value"], ["KEGG pathway", "hsa03320:PPAR signaling pathway", "5", "20", "8.49E−06"], ["hsa04152:AMPK signaling pathway", "4", "16", "0.001259508"], ["hsa04920:Adipocytokine signaling pathway", "3", "12", "0.006904311"], ["hsa04114:Oocyte meiosis", "3", "12", "0.025501685"]], "row_count": 5, "column_count": 5, "numeric_cells": 16, "header_rows": 1, "locator": "section[13]/table-wrap[2]#T4"}}, {"id": "asset:table:pmid:40826700:5", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:90d14b1db013428b50fc3f037f69e48753d681e14e016bef45cc1ed19e1773ec", "bytes": 379, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[14]/table-wrap[1]#T5", "version": null, "note": "Top 20 hub genes with degree >10.", "structure": {"pmcid": "PMC12366978", "section_index": 14, "section_title": "3.3. PPI network construction", "row_count": 5, "column_count": 2}, "table": {"label": "Table 5", "caption": "Top 20 hub genes with degree >10.", "rows": [["Degree of connectivity", "Hub genes"], ["28", "NUSAP1, NEK2"], ["26", "CDK1, CDC20, KIF20A, CEP55, HMMR, RRM2, BIRC5, MELK, AURKA, ASPM, PPARG"], ["24", "FGF2, CDCA3, DTL, LEP"], ["18", "CAV1, LPL, FABP4"]], "row_count": 5, "column_count": 2, "numeric_cells": 5, "header_rows": 1, "locator": "section[14]/table-wrap[1]#T5"}}], "gaps": ["asset:source:pmid:40826700 not verified"]}, "analysis": {"state": "absent", "methods": [], "targets": [], "gaps": ["method", "targets"]}, "capability": {"state": "absent", "requirements": [], "gaps": ["capability"]}, "readiness": {"state": "partial", "tier": null, "blocking_axis": null, "blocked_on": null, "axes": {}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:40826700", "asset:table:pmid:40826700:1", "asset:table:pmid:40826700:2", "asset:table:pmid:40826700:3", "asset:table:pmid:40826700:4", "asset:table:pmid:40826700:5"], "steps": ["read_published_estimate"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:40826700"]}, "gaps": ["corpus_record_absent"]}, "review": {"state": "partial", "machine_critique": {"status": "blocked", "providers": [{"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "2b7ba834a6b80ca9d613c6f5b08a1211e17b4410a3fb7b5225bced2e6e76a2e1", "source_hash": "f75f271b744a25d8c199261cfabab399c9ce4b7cec3527ec4bebd4617ad0600b", "raw_response_sha256": "sha256:01a7ecc0829610805763271b9f0949772aea462992f90eb09cef8c4ff45e2e61", "raw_response_chars": 68944}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "c8a444f319a13e960e712ef3416856c883c3204edd89f0c4313a3c3b41d12a79", "source_hash": "f75f271b744a25d8c199261cfabab399c9ce4b7cec3527ec4bebd4617ad0600b", "raw_response": "{\"parent_value\":4,\"unit\":\"potential biomarkers\",\"evidence\":\"Our present study identifies 4 potential biomarkers for BRCA including AURKA, DTL, NUSAP1, and RRM2.\",\"target_result\":\"The paper identifies 4 potential biomarkers for BRCA: AURKA, DTL, NUSAP1, and RRM2.\",\"number_stated\":true}", "reading": {"parent_value": 4, "unit": "potential biomarkers", "evidence": "Our present study identifies 4 potential biomarkers for BRCA including AURKA, DTL, NUSAP1, and RRM2.", "target_result": "The paper identifies 4 potential biomarkers for BRCA: AURKA, DTL, NUSAP1, and RRM2.", "number_stated": true, "source_locator": "chars 4572-4672 of source sha256 f75f271b744a25d8c199261cfabab399c9ce4b7cec3527ec4bebd4617ad0600b"}, "recorded_at": "2026-10-31T15:31:17.539022+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "f6257a4d266590702813d52b3c807b411a6bf701b594040050ec744f5a4e5296", "source_hash": "f75f271b744a25d8c199261cfabab399c9ce4b7cec3527ec4bebd4617ad0600b", "raw_response": "<think>We need answer JSON object only. Need determine single numerical result replication registered target headline numerical result paper states for main finding. Need parse task. Need choose likely 4 potential biomarkers? \"headline numerical result\" perhaps paper's main finding: identifies 4 potential biomarkers for BRCA. Need report headline number only, value paper itself states for registered target, unit paper prints. Evidence exact contiguous quote containing number; attribution via wording. Registered target: \"the headline numerical result the paper states for its main finding\". Source conclusion: \"Our present study identifies 4 potential biomarkers for BRCA including AURKA, DTL, NUSAP1, and RRM2.\" Likely parent_value 4, unit maybe \"potential biomarkers\" (unit must unit paper prints). Need formulate JSON. Could evidence quote exact sentence or clause. Unit likely \"potential biomarkers\". target_result perhaps \"4 potential biomarkers\" or sentence. Need infer expected extraction schema conventions. They ask \"Report the headline number only: the value the paper itself states for the registered target, not a value you calculated, converted, averaged or reconstructed. The unit must be the unit the paper prints. The evidence must be an exact, contiguous quotation from SOURCE TEXT that contains the number; do not shorten it, do not add an ellipsis and do not paraphrase it. Attribution may be carried by the text's own wording: a number may be attached to the target by a parenthetical list, by the word 'respectively', or by words that name the target directly. When that is how the text links them, quote the whole clause so a reader can check the attribution for themselves. If the text states no number for the registered target, set number_stated to false, leave parent_value at 0, leave unit and evidence empty, and say in target_result what the text does state instead. Never invent a source.\"\n\nWe need decide whether headline numerical result could be \"4\" biomarkers, versus 84 DEGs, 20 hub genes, 5 etc. Registered target deliberately generic perhaps expected headline main finding from conclusion = 4 potential biomarkers. They likely want number 4 and unit \"potential biomarkers\". Evidence exact quote: \"Our present study identifies 4 potential biomarkers for BRCA including AURKA, DTL, NUSAP1, and RRM2.\" This contains number and target. Need perhaps quote whole clause. JSON:\n{\n\"parent_value\":4,\n\"unit\":\"potential biomarkers\",\n\"evidence\":\"Our present study identifies 4 potential biomarkers for BRCA including AURKA, DTL, NUSAP1, and RRM2.\",\n\"target_result\":\"4 potential biomarkers\",\n\"number_stated\":true\n}\n\"Report headline number only\" means parent_value numerical, unit. target_result likely describe. Could unit be \"biomarkers\" rather than \"potential biomarkers\"? The unit paper prints perhaps \"potential biomarkers for BRCA\". They may want unit \"potential biomarkers\". We need ensure exact quote no citation markers. Yes.\n\nCould target be 5 hub genes expression levels significantly different among subtypes? Main abstract says \"results showed that expression levels of these 5 hub genes...\" But conclusion explicitly \"identifies 4 potential biomarkers\". \"single numerical result that a replication of registered target has to reproduce.\" The registered target phrase main finding. Headline numerical result likely count final validated biomarkers = 4. Unit must be unit. Let's analyze source and wording deeply.\n\nTitle: Identification of biomarkers and potential therapeutic targets of breast cancer using bioinformatics analysis. Abstract gives several numbers:\n- 43,780 deaths, 15% mortality rate\n- across 3 datasets\n- total 84 DEGs, 33 up, 51 down\n- top 20 key genes\n- expression levels of these 5 hub genes significantly different among subtypes\n- four hub genes finally identified via RT-qPCR\nConclusion: identifies 4 potential biomarkers.\n\nQuestion likely generated benchmark where target is semantic \"the headline numerical result the paper states for its main finding\", requiring choose count of final biomarkers. The explicit conclusion is strongest. Could \"headline numerical result\" refer to abstract's headline: 4 hub genes finally identified. Yes.\n\nNeed only JSON, valid. Unit perhaps \"potential biomarkers\" and target_result perhaps \"4 potential biomarkers for BRCA\". \"headline number only\" could mean don't include gene list in target_result? Evidence must exact full clause perhaps sentence. They ask report headline number only likely no other values. We can give evidence full sentence but includes no other numeric except 4. Good.\n\nCould evidence quote only clause: \"Our present study identifies 4 potential biomarkers for BRCA including AURKA, DTL, NUSAP1, and RRM2.\" exact. \"do not shorten it\" perhaps quote whole clause. That's exact sentence. Unit \"potential biomarkers\" is printed. target_result perhaps \"The paper identifies 4 potential biomarkers for BRCA.\" But they said report headline number only, perhaps target_result should be \"4 potential biomarkers for BRCA\".</think>\n\n{\"parent_value\":4,\"unit\":\"potential biomarkers\",\"evidence\":\"Our present study identifies 4 potential biomarkers for BRCA including AURKA, DTL, NUSAP1, and RRM2.\",\"target_result\":\"4 potential biomarkers for BRCA\",\"number_stated\":true}", "reading": {"parent_value": 4, "unit": "potential biomarkers", "evidence": "Our present study identifies 4 potential biomarkers for BRCA including AURKA, DTL, NUSAP1, and RRM2.", "target_result": "4 potential biomarkers for BRCA", "number_stated": true, "source_locator": "chars 4572-4672 of source sha256 f75f271b744a25d8c199261cfabab399c9ce4b7cec3527ec4bebd4617ad0600b"}, "recorded_at": "2026-10-31T15:31:23.746345+00:00"}], "agreement": false, "disagreements": [], "agreement_basis": {"policy": "decisive_fields", "decisive_fields": ["work_type", "number_stated", "parent_value", "unit"]}, "blinded": true}, "human_critique": {"status": "not_run", "reviewer": null, "signed_at": null, "conflict_checked": false, "commentary": null}, "stages": [{"key": "target_materials", "status": "pending", "reason": null, "evidence": null}, {"key": "independent_readings", "status": "blocked", "reason": "The independent readings are incomplete or disagree; the source evidence must resolve the difference.", "evidence": {"provider_errors": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "reason": "a quoted statement is absent from the supplied text", "raw_response": "{\"target_result\":\"4 potential biomarkers for BRCA: AURKA, DTL, NUSAP1, and RRM2\",\"work_type\":\"analysis_plus_physical_validation\",\"physical_methods\":[\"reverse transcription quantitative polymerase chain reaction\"],\"analysis_methods\":[\"Venn diagram analysis\",\"Gene Ontology enrichment analysis\",\"KEGG pathway enrichment analysis\",\"STRING protein-protein interaction network analysis\",\"Molecular Complex Detection\",\"CytoHubba\",\"Kaplan–Meier survival analysis\",\"GEPIA validation\",\"UALCAN validation\"],\"statistical_method\":\"Kaplan–Meier survival analysis\",\"method_evidence\":\"The survival analysis for the selected genes was conducted using the Kaplan–Meier Plotter online tool (https://kmplot.com/analysis/).\",\"repositories\":[{\"repository\":\"Gene Expression Omnibus\",\"accession\":\"GSE42568 and GSE5364\",\"data_description\":\"Gene expression datasets for BRCA used to identify differentially expressed genes.\",\"evidence\":\"The GSE42568 and GSE5364 datasets were obtained from the Gene Expression Omnibus database, and the Cancer Genome Atlas BRCA dataset was sourced from the Xena functional genomics platform.\",\"publicly_downloadable\":false},{\"repository\":\"Xena functional genomics platform\",\"accession\":\"Cancer Genome Atlas BRCA dataset\",\"data_description\":\"BRCA gene expression data from the Cancer Genome Atlas used in the differential-expression analysis.\",\"evidence\":\"The GSE42568 and GSE5364 datasets were obtained from the Gene Expression Omnibus database, and the Cancer Genome Atlas BRCA dataset was sourced from the Xena functional genomics platform.\",\"publicly_downloadable\":false}],\"availability_statement\":\"The paper states that GSE42568 and GSE5364 were obtained from the Gene Expression Omnibus database and that the Cancer Genome Atlas BRCA dataset was sourced from the Xena functional genomics platform, but it does not explicitly state whether the underlying data can be downloaded without an application, embargo, or request.\",\"data_on_request\":false,\"source_claims\":[\"A total of 84 overlapping differentially expressed genes were preliminarily screened, including 33 upregulated and 51 downregulated genes.\",\"The top 20 highly connected key genes were identified using Cytoscape software.\",\"Four hub genes (AURKA, DTL, NUSAP1, and RRM2) were identified through reverse transcription quantitative polymerase chain reaction.\",\"All four genes exhibited high expression levels in BRCA tissues compared with normal tissues.\",\"Patients with higher expression of AURKA, DTL, NUSAP1, or RRM2 had shorter overall survival, whereas patients with higher FGF2 expression had longer overall survival.\",\"The study identifies four potential biomarkers for BRCA and possible new treatment targets.\"],\"missing_information\":[\"The paper does not explicitly state that the repository data can be downloaded without an application, embargo, or request.\",\"The paper does not explicitly state that the repository data are available on request.\",\"The source text does not provide a separate statistical test for the tissue-expression comparison of the four genes.\"],\"evidence_spans\":[\"The GSE42568 and GSE5364 datasets were obtained from the Gene Expression Omnibus database, and the Cancer Genome Atlas BRCA dataset was sourced from the Xena functional genomics platform.\",\"A total of 84 overlapping differentially expressed genes were preliminarily screened at the initial stage, including 33 upregulated and 51 downregulated genes.\",\"The top 20 highly connected key genes were identified subsequently using Cytoscape software.\",\"Four hub genes (AURKA, DTL, NUSAP1, and RRM2) were finally identified through reverse transcription quantitative polymerase chain reaction.\",\"When compared to normal tissues, all of these genes exhibit high expression levels in BRCA tissues.\",\"The results indicated that patients with higher expression levels of AURKA (HR [hazard ratio] = 1.65, P < .001), DTL (HR = 1.52, P < .001), NUSAP1 (HR = 1.65, P < .001), and RRM2 (HR = 1.57, P < .001) had shorter overall survival, whereas patients with higher Fibroblast Growth Factor 2 (FGF2) expression (HR = 0.8, P = .019) had longer overall survival (Fig. 6).\",\"Our present study identifies 4 potential biomarkers for BRCA including AURKA, DTL, NUSAP1, and RRM2.\"]}"}]}}, {"key": "source_resolution", "status": "pending", "reason": null, "evidence": null}, {"key": "protocol_reconstruction", "status": "pending", "reason": null, "evidence": null}, {"key": "control_execution", "status": "pending", "reason": null, "evidence": null}, {"key": "control_comparison", "status": "pending", "reason": null, "evidence": null}, {"key": "publication", "status": "pending", "reason": null, "evidence": null}], "gaps": ["review.human_critique", "review.machine_critique.blocked"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "package:307aa9a2ce955d64b7cba6ac161d2a087cd7c1e97131ece96be0448f73bc2865", "type": "sep_package", "label": "SEP v1 package for pmid:40826700"}], "activities": [{"id": "activity:conversion:pmid:40826700", "type": "conversion", "used": ["package:307aa9a2ce955d64b7cba6ac161d2a087cd7c1e97131ece96be0448f73bc2865"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:minimax", "type": "model", "label": "minimax"}, {"id": "agent:minimax_alt", "type": "model", "label": "minimax_alt"}, {"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}], "source_run_id": "run-20261023T122449232913", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:40826700", "parent_hash": "sha256:1207e5621b4003205bee6c87d5a22a645ece1e82bea6c9fd08ccb53fae18e434", "fork_of": null, "generation": 2}, "gaps": ["abstract", "asset:source:pmid:40826700 not verified", "authors", "capability", "corpus_record_absent", "execution.not_run", "method", "review.human_critique", "review.machine_critique.blocked", "step:obtain_source_data blocked on data:not_downloaded", "step:run_analysis blocked on no owned computational capability is bound to this experiment", "step:run_analysis input 'materials:the source data behind the published result in pmid:40826700' does not resolve to a declared asset", "targets"]},"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":"2026-11-04T04:47:22+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}}}