{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39430830", "kind": "science-record", "revision": 3, "content_hash": "sha256:3605cdfe3005d2223ee3caf550dadbcc5e9f45c6ba8e89e93f5a2f947f0ea0d8", "created_at": "2026-11-01T20:29:41Z", "updated_at": "2026-11-01T22:12:59Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Construction and validation of senescence risk score signature as a novel biomarker in liver hepatocellular carcinoma: a bioinformatic analysis.", "doi": "10.21037/tcr-23-2373", "pmid": "39430830", "authors": ["Tianqi Lai", "Feilong Li", "Leyang Xiang", "Zhilong Liu", "Qiang Li", "Mingrong Cao", "Jian Sun", "Youzhu Hu", "Tongzheng Liu", "Junjie Liang"], "journal": "Translational cancer research", "year": 2024, "abstract": "Background: Globally, liver cancer as one of the most frequent fatal malignancies, hits hard and fast. And the lack of effective treatments for liver hepatocellular carcinoma (LIHC), activates the researchers to promote promising precision medicine. Interestingly, emerging evidence proves that cellular senescence is involved in the progression of cancers and is recognized for its hallmark-promoting capabilities. Hence, efforts have been made to construct and validate the senescence risk score signature (SRSS) model as a novel prognostic biomarker for LIHC.\nMethods: The existing databases were mined for the following bioinformatics analyses. GSE22405, GSE57957, and senescence-related genes (SRGs) from public databases were utilized as a training set and the validation set was constituted by LIHC and pancreatic adenocarcinoma (PAAD) from The Cancer Genome Atlas (TCGA). After overlapping differentially expressed genes (DEGs) with SRGs, differentially expressed SRGs were identified with the progression of liver cancer through univariate and multivariate Cox regression and enrichment analyses. The model that utilized three SRGs was constructed using the least absolute shrinkage and selection operator (LASSO) regression algorithm. Next, to evaluate the predictive performance of the SRSS model, the overall survival (OS) and survival rates were assessed through Kaplan-Meier (KM) and the receiver operating characteristic (ROC) curves. The predictive value for LIHC prognosis was further evaluated by capitalizing on risk score, nomograms, decision curve analysis (DCA) curves, and clinical information including tumor stages, gender, age, and race.\nResults: DEGs were revealed as enriching in multiple tumor-related biological processes (BPs) and pathways. IGFBP3, SOCS2, and RACGAP1 were identified as the three considerable SRGs for the model. The high-risk group had a worse prognosis [both hazard ratio (HR) >1, P<0.001] and ROC curves showed a reliable predictive model with area under the curve (AUC) predictive values ranging from 0.673-0.816 for different-year survival rates respectively. The univariate and multivariate Cox regression analyses exhibited that risk score was the only credible prognostic predictor (HR >1, P<0.001) among clinical features such as tumor stage, age, etc., in LIHC. The nomograms, and DCA curves, combined with multiple clinical information, proved that the predictive ability of SRSS was strongest, followed by nomogram and traditional tumor node metastasis (TNM) stage was the weakest.\nConclusions: In summary, comprehensive analyses supported that the SRSS model can better predict survival and risk in LIHC patients. Promisingly, it may point out a brand-new direction for LIHC therapy.", "claims": [{"id": "claim-method", "statement": "The model that utilized three SRGs was constructed using the least absolute shrinkage and selection operator (LASSO) regression algorithm.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39430830", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The model that utilized three SRGs was constructed using the least absolute shrinkage and selection operator (LASSO) regression algorithm."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The GSE22405 dataset contained 24 non-tumor and 24 LIHC samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39430830", "locator": "sections[5] \"Datasets and data preprocessing\" paragraph 2", "quote": "The GSE22405 dataset contained 24 non-tumor and 24 LIHC samples."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Using GSE22405, GSE57957, and public senescence-related genes for training and TCGA LIHC and PAAD data for validation, the study constructed an SRSS model using three senescence-related genes selected by LASSO regression.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39430830", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "GSE22405, GSE57957, and senescence-related genes (SRGs) from public databases were utilized as a training set and the validation set was constituted by LIHC and pancreatic adenocarcinoma (PAAD) from The Cancer Genome Atlas (TCGA)."}, {"asset": "source:pmid:39430830", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The model that utilized three SRGs was constructed using the least absolute shrinkage and selection operator (LASSO) regression algorithm."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Using GSE22405, GSE57957, and public senescence-related genes for training and TCGA LIHC and PAAD data for validation, the study constructed an SRSS model using three senescence-related genes selected by LASSO regression.", "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:39430830"], "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:GSE22405"], "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:GSE22405"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39430830", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/tcr-23-2373", "sha256": "sha256:59a1efb116ea8636003e65e1592e820c29d79c0e59fbaaff5c531226e6fc9b5b", "bytes": 30527, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.21037/tcr-23-2373", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11483424", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE22405", "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=GSE22405", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE22405", "version": null, "note": "The GSE22405 dataset contained 24 non-tumor and 24 LIHC samples.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The GSE22405 dataset contained 24 non-tumor and 24 LIHC samples.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM557089", "GSM557090", "GSM557091", "GSM557092", "GSM557093", "GSM557094", "GSM557095", "GSM557096", "GSM557097", "GSM557098", "GSM557099", "GSM557100", "GSM557101", "GSM557102", "GSM557103", "GSM557104", "GSM557105", "GSM557106", "GSM557107", "GSM557108", "GSM557109", "GSM557110", "GSM557111", "GSM557112", "GSM557113", "GSM557114", "GSM557115", "GSM557116", "GSM557117", "GSM557118", "GSM557119", "GSM557120", "GSM557121", "GSM557122", "GSM557123", "GSM557124", "GSM557125", "GSM557126", "GSM557127", "GSM557128", "GSM557129", "GSM557130", "GSM557131", "GSM557132", "GSM557133", "GSM557134", "GSM557135", "GSM557136"], "sample_count": 48, "group_sizes": null, "group_sizes_basis": null, "platform": "10553", "taxon": "Homo sapiens", "title": "Gene expression profiling of liver cancers", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE57957", "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=GSE57957", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE57957", "version": null, "note": "The GSE22405 dataset contained 24 non-tumor and 24 LIHC samples.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The GSE22405 dataset contained 24 non-tumor and 24 LIHC samples.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM1398645", "GSM1398646", "GSM1398647", "GSM1398648", "GSM1398649", "GSM1398650", "GSM1398651", "GSM1398652", "GSM1398653", "GSM1398654", "GSM1398655", "GSM1398656", "GSM1398657", "GSM1398658", "GSM1398659", "GSM1398660", "GSM1398661", "GSM1398662", "GSM1398663", "GSM1398664", "GSM1398665", "GSM1398666", "GSM1398667", "GSM1398668", "GSM1398669", "GSM1398670", "GSM1398671", "GSM1398672", "GSM1398673", "GSM1398674", "GSM1398675", "GSM1398676", "GSM1398677", "GSM1398678", "GSM1398679", "GSM1398680", "GSM1398681", "GSM1398682", "GSM1398683", "GSM1398684", "GSM1398685", "GSM1398686", "GSM1398687", "GSM1398688", "GSM1398689", "GSM1398690", "GSM1398691", "GSM1398692", "GSM1398693", "GSM1398694", "GSM1398695", "GSM1398696", "GSM1398697", "GSM1398698", "GSM1398699", "GSM1398700", "GSM1398701", "GSM1398702", "GSM1398703", "GSM1398704", "GSM1398705", "GSM1398706", "GSM1398707", "GSM1398708", "GSM1398709", "GSM1398710", "GSM1398711", "GSM1398712", "GSM1398713", "GSM1398714", "GSM1398715", "GSM1398716", "GSM1398717", "GSM1398718", "GSM1398719", "GSM1398720", "GSM1398721", "GSM1398722"], "sample_count": 78, "group_sizes": null, "group_sizes_basis": null, "platform": "10558", "taxon": "Homo sapiens", "title": "Expression profile of Hepatocellular Carcinoma", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE22405 not downloaded", "asset:data:geo:GSE22405 licence not read", "asset:data:geo:GSE57957 not downloaded", "asset:data:geo:GSE57957 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Kaplan-Meier"}}, {"id": "method-2", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Cox regression"}}, {"id": "method-3", "family": "model_calibration", "specific": "decision_curve", "label": "Model calibration / clinical utility", "dsl_operations": ["calibration_bins", "net_benefit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["predictions_and_outcomes"], "evidence": {"score": 0.7, "band": "medium", "quote": "decision curve analysis"}}, {"id": "method-4", "family": null, "specific": null, "label": "least absolute shrinkage and selection operator (LASSO) regression", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The model that utilized three SRGs was constructed using the least absolute shrinkage and selection operator (LASSO) regression algorithm."}}], "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": ["survival_km"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: kaplan_meier."}, "capability": {"tier": "R1", "capability_id": 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE22405", "GSE57957"], "resolved_accessions": ["GSE22405", "GSE57957"], "statements": ["The GSE22405 dataset contained 24 non-tumor and 24 LIHC samples."], "basis": "The paper names GSE22405, GSE57957 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": ["survival_km"], "assets": ["source:pmid:39430830", "data:geo:GSE22405"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE22405"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:36:05Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 5, "usage": {"prompt_tokens": 8790, "completion_tokens": 1966, "cached_tokens": 128}}, "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:39430830", "type": "paper", "label": "pmid:39430830"}, {"id": "source:pmid:39430830", "type": "manuscript", "label": "PMID 39430830 full text"}, {"id": "data:geo:GSE22405", "type": "dataset", "label": "GEO GSE22405"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:39430830", "type": "paper", "label": "pmid:39430830"}, {"id": "source:pmid:39430830", "type": "manuscript", "label": "PMID 39430830 full text"}, {"id": "data:geo:GSE22405", "type": "dataset", "label": "GEO GSE22405"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-39430830", "type": "extraction", "used": ["source:pmid:39430830"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE22405", "type": "accession_resolution", "used": ["data:geo:GSE22405"], "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:39430830", "parent_hash": "sha256:27ffa110607323c63a46fc275cb161ef8dc2a89fb744d6e6e3e81e8d6097e5d0", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE22405 licence not read", "asset:data:geo:GSE22405 not downloaded", "asset:data:geo:GSE57957 licence not read", "asset:data:geo:GSE57957 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["survival_km"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.7, "evidence": ["Kaplan-Meier"], "order_basis": "analysis_only", "id": "assay:1"}]},"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":"2026-11-04T01:42:59+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}}}