{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40821971", "kind": "science-record", "revision": 3, "content_hash": "sha256:65395142619fcb6264e0fc2dc3e92ca0fd260054d060c8d31b7e7699b23410d1", "created_at": "2026-11-01T20:30:54Z", "updated_at": "2026-11-01T22:14:34Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of hub genes and prediction of the ceRNA network in adult sepsis.", "doi": "10.7717/peerj.19619", "pmid": "40821971", "authors": ["Kangyi Xue", "Kan Wu", "Haoxian Luo", "Haihua Luo", "Zhaoqian Zhong", "Fen Li", "Lei Li", "Li Chen"], "journal": "PeerJ", "year": 2025, "abstract": "Background: Sepsis refers to a dysregulated host immune response to infection. It carries a high risk of morbidity and mortality, and its pathogenesis has yet to be fully elucidated. The main aim of this study was to identify prognostic hub genes for sepsis and to predict a competitive endogenous RNA (ceRNA) network that regulates the hub genes.\nMethods: Six transcriptome datasets from the peripheral blood of septic patients were retrieved from the Gene Expression Omnibus (GEO) database. The robust rank aggregation (RRA) method was used to screen differentially expressed genes (DEGs) across these datasets. A comprehensive bioinformatics investigation was conducted, encompassing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses using the \"clusterProfiler\" package in R, as well as gene set enrichment analysis (GSEA) to further elucidate the biological functions and pathways associated with the DEGs. Weighted gene co-expression network analysis (WGCNA) was performed to identify a module significantly associated with sepsis. Integration of this module with protein-protein interaction (PPI) network analysis facilitated the identification of five hub genes. These hub genes were subsequently validated using an independent dataset and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis of peripheral blood samples from septic patients. The prognostic values of these hub genes were assessed via receiver operating characteristic (ROC) curve analysis. Finally, a ceRNA network regulating the prognostic hub genes was constructed by integrating data from a literature review as well as five online databases.\nResults: RRA analysis identified 164 DEGs across six training cohorts. Bioinformatics analyses revealed concurrent hyperinflammation and immunosuppression in sepsis patients. Five hub genes were identified via WGCNA and PPI network analysis, and their differential expression was verified by the validation dataset (GSE28750) and RT-qPCR analysis in the peripheral blood of septic patients. ROC analysis confirmed four hub genes with prognostic value, and a ceRNA network was predicted to elucidate their regulatory mechanisms.\nConclusion: This study identified four hub genes (CLEC4D, GPR84, S100A12, and HK3) with significant prognostic value in sepsis and predicted a ceRNA network (NEAT1-hsa-miR-495-3p-ELF1) regulating their expression. The integrated analysis reconfirmed the concurrent presence of hyperinflammation and immunosuppression in hospitalized sepsis patients. These findings enhance the understanding of sepsis pathogenesis and identify potential therapeutic targets.", "claims": [{"id": "claim-method", "statement": "Statistically changed genes and differentially expressed genes (DEGs) were screened using the robust rank aggregation (RRA) method, which is an unbiased and effective approach for integrating data from diverse chip platforms using a comprehensive ranking list algorithm (Jia & Zhai, 2019; Yan et al., 2018).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40821971", "locator": "sections[4] \"Robust rank aggregation analysis\" paragraph 2", "quote": "Statistically changed genes and differentially expressed genes (DEGs) were screened using the robust rank aggregation (RRA) method, which is an unbiased and effective approach for integrating data from diverse chip platforms using a comprehensive ranking list algorithm (Jia & Zhai, 2019; Yan et al., 2018)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets are available at GEO: GSE137340, GSE69063, GSE69528, GSE54514, GSE57065, GSE95233, and GSE28570.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40821971", "locator": "sections[29] \"Additional Information and Declarations\" paragraph 6", "quote": "The datasets are available at GEO: GSE137340, GSE69063, GSE69528, GSE54514, GSE57065, GSE95233, and GSE28570."}], "state": "complete"}, {"id": "claim-target-result", "statement": "This study identified four hub genes (CLEC4D, GPR84, S100A12, and HK3) with significant prognostic value in sepsis and predicted a ceRNA network (NEAT1-hsa-miR-495-3p-ELF1) regulating their expression.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40821971", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "This study identified four hub genes (CLEC4D, GPR84, S100A12, and HK3) with significant prognostic value in sepsis and predicted a ceRNA network (NEAT1-hsa-miR-495-3p-ELF1) regulating their expression."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "This study identified four hub genes (CLEC4D, GPR84, S100A12, and HK3) with significant prognostic value in sepsis and predicted a ceRNA network (NEAT1-hsa-miR-495-3p-ELF1) regulating their expression.", "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:40821971"], "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:GSE137340"], "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": {"n_clusters": "clustering tree showing 11 cluster modules"}, "inputs": ["data:geo:GSE137340"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40821971", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.7717/peerj.19619", 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available at GEO: GSE137340, GSE69063, GSE69528, GSE54514, GSE57065, GSE95233, and GSE28570.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets are available at GEO: GSE137340, GSE69063, GSE69528, GSE54514, GSE57065, GSE95233, and GSE28570.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1702888", "GSM1702889", "GSM1702890", "GSM1702891", "GSM1702892", "GSM1702893", "GSM1702894", "GSM1702895", "GSM1702896", "GSM1702897", "GSM1702898", "GSM1702899", "GSM1702900", "GSM1702901", "GSM1702902", "GSM1702903", "GSM1702904", "GSM1702905", "GSM1702906", "GSM1702907", "GSM1702908", "GSM1702909", "GSM1702910", "GSM1702911", "GSM1702912", "GSM1702913", "GSM1702914", "GSM1702915", "GSM1702916", "GSM1702917", "GSM1702918", "GSM1702919", "GSM1702920", "GSM1702921", "GSM1702922", "GSM1702923", "GSM1702924", "GSM1702925", "GSM1702926", "GSM1702927", "GSM1702928", "GSM1702929", "GSM1702930", 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"GSM2500457", "GSM2500458", "GSM2500459", "GSM2500460", "GSM2500461", "GSM2500462", "GSM2500463", "GSM2500464", "GSM2500465", "GSM2500466", "GSM2500467", "GSM2500468", "GSM2500469", "GSM2500470", "GSM2500471", "GSM2500472"], "sample_count": 124, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Fractalkine receptor CX3CR1 and leukocyte Ig-like receptor B2 LILRB2 are prognostic biomarkers in septic shock", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE137340 not downloaded", "asset:data:geo:GSE137340 licence not read", "asset:data:geo:GSE28750 not downloaded", "asset:data:geo:GSE28750 licence not read", "asset:data:geo:GSE54514 not downloaded", "asset:data:geo:GSE54514 licence not read", "asset:data:geo:GSE57065 not downloaded", "asset:data:geo:GSE57065 licence not read", "asset:data:geo:GSE69063 not downloaded", "asset:data:geo:GSE69063 licence not read", "asset:data:geo:GSE69528 not downloaded", "asset:data:geo:GSE69528 licence not read", "asset:data:geo:GSE95233 not downloaded", "asset:data:geo:GSE95233 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "clustering", "specific": "hierarchical", "label": "Clustering", "dsl_operations": ["hierarchical_cluster"], "missing_operations": [], "expressible": true, "parameters": {"n_clusters": "clustering tree showing 11 cluster modules"}, "data_shapes": ["feature_matrix"], "evidence": {"score": 0.8, "band": "high", "quote": "Hierarchical clustering"}}, {"id": "method-2", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "protein-protein interaction"}}, {"id": "method-3", "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"}}, {"id": "method-4", "family": "diagnostic_evaluation", "specific": "roc", "label": "Diagnostic test evaluation", "dsl_operations": ["confusion_counts", "roc_curve", "sensitivity_specificity", "solve_confusion_matrix", "classification_metrics", "published_precision_envelope"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["reference_standard_and_test"], "evidence": {"score": 0.7, "band": "medium", "quote": "ROC analysis"}}, {"id": "method-5", "family": null, "specific": null, "label": "robust rank aggregation (RRA) method", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Statistically changed genes and differentially expressed genes (DEGs) were screened using the robust rank aggregation (RRA) method, which is an unbiased and effective approach for integrating data from diverse chip platforms using a comprehensive ranking list algorithm (Jia & Zhai, 2019; Yan et al., 2018)."}}], "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": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["hierarchical_cluster"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: hierarchical."}, "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": ["GSE137340", "GSE69063", "GSE69528", "GSE54514", "GSE57065", "GSE95233", "GSE28750"], "resolved_accessions": ["GSE137340", "GSE69063", "GSE69528", "GSE54514", "GSE57065", "GSE95233", "GSE28750"], "statements": ["The datasets are available at GEO: GSE137340, GSE69063, GSE69528, GSE54514, GSE57065, GSE95233, and GSE28570."], "basis": "The paper names GSE137340, GSE69063, GSE69528, GSE54514, GSE57065, GSE95233, GSE28750 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": ["hierarchical_cluster"], "assets": ["source:pmid:40821971", "data:geo:GSE137340"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE137340"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:59:38Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 13948, "completion_tokens": 1998, "cached_tokens": 264}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:40821971", "type": "paper", "label": "pmid:40821971"}, {"id": "source:pmid:40821971", "type": "manuscript", "label": "PMID 40821971 full text"}, {"id": "data:geo:GSE137340", "type": "dataset", "label": "GEO GSE137340"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:40821971", "type": "paper", "label": "pmid:40821971"}, {"id": "source:pmid:40821971", "type": "manuscript", "label": "PMID 40821971 full text"}, {"id": "data:geo:GSE137340", "type": "dataset", "label": "GEO GSE137340"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-40821971", "type": "extraction", "used": ["source:pmid:40821971"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE137340", "type": "accession_resolution", "used": ["data:geo:GSE137340"], "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:40821971", "parent_hash": "sha256:b05802d5062e3c088ed36deee9961bbad2b31e4360148c596d4ae7003dcde346", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE137340 licence not read", "asset:data:geo:GSE137340 not downloaded", "asset:data:geo:GSE28750 licence not read", "asset:data:geo:GSE28750 not downloaded", "asset:data:geo:GSE54514 licence not read", "asset:data:geo:GSE54514 not downloaded", "asset:data:geo:GSE57065 licence not read", "asset:data:geo:GSE57065 not downloaded", "asset:data:geo:GSE69063 licence not read", "asset:data:geo:GSE69063 not downloaded", "asset:data:geo:GSE69528 licence not read", "asset:data:geo:GSE69528 not downloaded", "asset:data:geo:GSE95233 licence not read", "asset:data:geo:GSE95233 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": 0.99, "evidence": [". The present study systematically retrieved microarray datasets based on the following terms: ‘Seps", "rms: ‘Sepsis’, ‘Adult’, ‘Homo sapiens’, and ‘Microarray’. Datasets were acquired based on the follow", "or Bioconductor (https://bioconductor.org/). Microarray information. Peripheral blood samples from p"], "order_basis": "paper_text_order:2976", "id": "assay:1"}, {"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["l care and housing SPF-grade C57BL/6 healthy mice were purchased from Southern Medical University.", "days prior to the start of the experiments. Mice were provided ordinary Specific Pathogen Free (SP", "water freely throughout the experiment. All mice were housed in units of equal size and material a", "tory Animals. Sixteen SPF-grade male C57BL/6 mice were randomly divided into two groups, cecal liga"], "order_basis": "paper_text_order:4729", "id": "assay:2"}, {"role": "analysis", "definition_id": "clustering", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["hierarchical_cluster"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["Hierarchical clustering"], "order_basis": "consumes_earlier_output", "id": "assay:3"}]},"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":"2026-11-04T02:36:11+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}}}