{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35898492", "kind": "science-record", "revision": 4, "content_hash": "sha256:56e08cd7fdf971a71218d9ab787b72b28c006074c6058b1c9da0bb83f8ce6e2d", "created_at": "2026-11-01T18:14:59Z", "updated_at": "2026-11-01T22:07:09Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A Four-Cell-Senescence-Regulator-Gene Prognostic Index Verified by Genome-Wide CRISPR Can Depict the Tumor Microenvironment and Guide Clinical Treatment of Bladder Cancer.", "doi": "10.3389/fimmu.2022.908068", "pmid": "35898492", "authors": ["Jian-Xuan Sun", "Chen-Qian Liu", "Jin-Zhou Xu", "Ye An", "Meng-Yao Xu", "Xing-Yu Zhong", "Na Zeng", "Si-Yang Ma", "Hao-Dong He", "Zong-Biao Zhang", "Shao-Gang Wang", "Qi-Dong Xia"], "journal": "Frontiers in immunology", "year": 2022, "abstract": "Bladder cancer (BCa) is the 10th most commonly diagnosed cancer worldwide, and cellular senescence is defined as a state of permanent cell cycle arrest and considered to play important roles in the development and progression of tumor. However, the comprehensive effect of senescence in BCa has not ever been systematically evaluated. Using the genome-wide CRISPR screening data acquired from DepMap (Cancer Dependency Map), senescence genes from the CellAge database, and gene expression data from The Cancer Genome Atlas (TCGA), we screened out 12 senescence genes which might play critical roles in BCa. A four-cell-senescence-regulator-gene prognostic index was constructed using the least absolute shrinkage and selection operator (LASSO) and multivariate COX regression model. The transcriptomic data and clinical information of BCa patients were downloaded from TCGA and Gene Expression Omnibus (GEO). We randomly divided the patients in TCGA cohort into training and testing cohorts and calculated the risk score according to the expression of the four senescence genes. The validity of this risk score was validated in the testing cohort (TCGA) and validation cohort (GSE13507). The Kaplan-Meier curves revealed a significant difference in the survival outcome between the high- and low-risk score groups. A nomogram including the risk score and other clinical factors (age, gender, stage, and grade) was established with better predictive capacity of OS in 1, 3, and 5 years. Besides, we found that patients in the high-risk group had higher tumor mutation burden (TMB); lower immune, stroma, and ESTIMATE scores; higher tumor purity; aberrant immune functions; and lower expression of immune checkpoints. We also performed gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) to investigate the interaction between risk score and hallmark pathways and found that a high risk score was connected with activation of senescence-related pathways. Furthermore, we found that a high risk score was related to better response to immunotherapy and chemotherapy. In conclusion, we identified a four-cell-senescence-regulator-gene prognostic index in BCa and investigated its relationship with TMB, the immune landscape of tumor microenvironment (TME), and response to immunotherapy and chemotherapy, and we also established a nomogram to predict the prognosis of patients with BCa.", "claims": [{"id": "claim-method", "statement": "The least absolute shrinkage and selection operator (LASSO) method was conducted in the training group to screen the appropriate variables of the above 11 ECSRGs. Following this, the multivariate cox regression of the left variables was performed in the training group to establish a prognostic cell senescence index (PCSI).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35898492", "locator": "sections[5] \"Elimination of the Batch Effects, Sample Random Grouping, Construction, and Verification of the Prognostic Cell Senescence Index\" paragraph 2", "quote": "The least absolute shrinkage and selection operator (LASSO) method was conducted in the training group to screen the appropriate variables of the above 11 ECSRGs. Following this, the multivariate cox regression of the left variables was performed in the training group to establish a prognostic cell senescence index (PCSI)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35898492", "locator": "sections[17] \"Data Availability Statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material ."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Meta-analysis across the training, testing, and validation cohorts showed that the four-gene risk score had a pooled hazard ratio of 1.33 (95% CI = 1.07–1.66, P = 0.06).", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "Besides, the result of meta-analysis based on the three cohorts illustrated that the risk score was in good validity (HR = 1.33, 95% CI = 1.07–1.66, P = 0.06) ( Figure 3N )."}, "evidence": [{"asset": "source:pmid:35898492", "locator": "sections[10] \"Construction and Verification of the Prognostic Cell Senescence Index\" paragraph 2", "quote": "Besides, the result of meta-analysis based on the three cohorts illustrated that the risk score was in good validity (HR = 1.33, 95% CI = 1.07–1.66, P = 0.06) ( Figure 3N )."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Meta-analysis across the training, testing, and validation cohorts showed that the four-gene risk score had a pooled hazard ratio of 1.33 (95% CI = 1.07–1.66, P = 0.06).", "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:35898492"], "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:GSE13507"], "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:GSE13507"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35898492", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2022.908068", "sha256": "sha256:5a42460989e61d4f3287fc2ccefdc58335c6a88bd7f3e6c9d90bad30b4e0ff01", "bytes": 49312, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2022.908068", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9312376", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE13507", "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=GSE13507", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE13507", "version": null, "note": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM340537", "GSM340538", "GSM340539", "GSM340540", "GSM340541", "GSM340542", "GSM340543", "GSM340544", "GSM340545", "GSM340546", "GSM340547", "GSM340548", "GSM340549", "GSM340550", "GSM340551", "GSM340552", "GSM340553", "GSM340554", "GSM340555", "GSM340556", "GSM340557", "GSM340558", "GSM340559", "GSM340560", "GSM340561", "GSM340562", "GSM340563", "GSM340564", "GSM340565", "GSM340566", "GSM340567", "GSM340568", "GSM340569", "GSM340570", "GSM340571", "GSM340572", "GSM340573", "GSM340574", "GSM340575", "GSM340576", "GSM340577", "GSM340578", "GSM340579", "GSM340580", "GSM340581", "GSM340582", "GSM340583", "GSM340584", "GSM340585", "GSM340586", "GSM340587", "GSM340588", "GSM340589", "GSM340590", "GSM340591", "GSM340592", "GSM340593", "GSM340594", "GSM340595", "GSM340596", "GSM340597", "GSM340598", "GSM340599", "GSM340600", "GSM340601", "GSM340602", "GSM340603", "GSM340604", "GSM340605", "GSM340606", "GSM340607", "GSM340608", "GSM340609", "GSM340610", "GSM340611", "GSM340612", "GSM340613", "GSM340614", "GSM340615", "GSM340616", "GSM340617", "GSM340618", "GSM340619", "GSM340620", "GSM340621", "GSM340622", "GSM340623", "GSM340624", "GSM340625", "GSM340626", "GSM340627", "GSM340628", "GSM340629", "GSM340630", "GSM340631", "GSM340632", "GSM340633", "GSM340634", "GSM340635", "GSM340636", "GSM340637", "GSM340638", "GSM340639", "GSM340640", "GSM340641", "GSM340642", "GSM340643", "GSM340644", "GSM340645", "GSM340646", "GSM340647", "GSM340648", "GSM340649", "GSM340650", "GSM340651", "GSM340652", "GSM340653", "GSM340654", "GSM340655", "GSM340656", "GSM340657", "GSM340658", "GSM340659", "GSM340660", "GSM340661", "GSM340662", "GSM340663", "GSM340664", "GSM340665", "GSM340666", "GSM340667", "GSM340668", "GSM340669", "GSM340670", "GSM340671", "GSM340672", "GSM340673", "GSM340674", "GSM340675", "GSM340676", "GSM340677", "GSM340678", "GSM340679", "GSM340680", "GSM340681", "GSM340682", "GSM340683", "GSM340684", "GSM340685", "GSM340686", "GSM340687", "GSM340688", "GSM340689", "GSM340690", "GSM340691", "GSM340692", "GSM340693", "GSM340694", "GSM340695", "GSM340696", "GSM340697", "GSM340698", "GSM340699", "GSM340700", "GSM340701", "GSM340702", "GSM340703", "GSM340704", "GSM340705", "GSM340706", "GSM340707", "GSM340708", "GSM340709", "GSM340710", "GSM340711", "GSM340712", "GSM340713", "GSM340714", "GSM340715", "GSM340716", "GSM340717", "GSM340718", "GSM340719", "GSM340720", "GSM340721", "GSM340722", "GSM340723", "GSM340724", "GSM340725", "GSM340726", "GSM340727", "GSM340728", "GSM340729", "GSM340730", "GSM340731", "GSM340732", "GSM340733", "GSM340734", "GSM340735", "GSM340736", "GSM340737", "GSM340738", "GSM340739", "GSM340740", "GSM340741", "GSM340742", "GSM340743", "GSM340744", "GSM340745", "GSM340746", "GSM340747", "GSM340748", "GSM340749", "GSM340750", "GSM340751", "GSM340752", "GSM340753", "GSM340754", "GSM340755", "GSM340756", "GSM340757", "GSM340758", "GSM340759", "GSM340760", "GSM340761", "GSM340762", "GSM340763", "GSM340764", "GSM340765", "GSM340766", "GSM340767", "GSM340768", "GSM340769", "GSM340770", "GSM340771", "GSM340772", "GSM340773", "GSM340774", "GSM340775", "GSM340776", "GSM340777", "GSM340778", "GSM340779", "GSM340780", "GSM340781", "GSM340782", "GSM340783", "GSM340784", "GSM340785", "GSM340786", "GSM340787", "GSM340788", "GSM340789", "GSM340790", "GSM340791", "GSM340792"], "sample_count": 256, "group_sizes": null, "group_sizes_basis": null, "platform": "6102", "taxon": "Homo sapiens", "title": "Predective Value of Prognosis-Related Gene Expression Study in Primary Bladder Cancer", "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:GSE13507 not downloaded", "asset:data:geo:GSE13507 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "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": 1.0, "band": "verbatim", "quote": "The least absolute shrinkage and selection operator (LASSO) method was conducted in the training group to screen the appropriate variables of the above 11 ECSRGs. Following this, the multivariate cox regression of the left variables was performed in the training group to establish a prognostic cell senescence index (PCSI)."}}, {"id": "method-2", "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-3", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "log-rank"}}, {"id": "method-4", "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": 0.8, "band": "high", "quote": "PPI"}}, {"id": "method-5", "family": "contingency_analysis", "specific": "chi_square", "label": "Categorical (contingency table) analysis", "dsl_operations": ["chi_square_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["categorical_cross_tabulation"], "evidence": {"score": 0.8, "band": "high", "quote": "χ2"}}], "targets": [{"id": "target-published-estimate", "claim_id": "claim-target-result", "operation": "build_graph", "expected_value": 95.0, "unit": "per cent", "tolerance": null, "state": "complete", "note": "The published estimate as the reader quoted it from the paper. 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A run that reproduces the effect is judged against this threshold."}], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "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": ["GSE13507"], "resolved_accessions": ["GSE13507"], "statements": ["The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material ."], "basis": "The paper names GSE13507 in Gene Expression Omnibus and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["cox_ph"], "assets": ["source:pmid:35898492", "data:geo:GSE13507"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE13507"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T17:57:36Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 12885, "completion_tokens": 1615, "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:35898492", "type": "paper", "label": "pmid:35898492"}, {"id": "source:pmid:35898492", "type": "manuscript", "label": "PMID 35898492 full text"}, {"id": "data:geo:GSE13507", "type": "dataset", "label": "GEO GSE13507"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:35898492", "type": "paper", "label": "pmid:35898492"}, {"id": "source:pmid:35898492", "type": "manuscript", "label": "PMID 35898492 full text"}, {"id": "data:geo:GSE13507", "type": "dataset", "label": "GEO GSE13507"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-35898492", "type": "extraction", "used": ["source:pmid:35898492"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE13507", "type": "accession_resolution", "used": ["data:geo:GSE13507"], "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:35898492", "parent_hash": "sha256:cd95d740cc941c7a39e71819cdd511a62ce79cdeebbf4489be76397f6434c5ef", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE13507 licence not read", "asset:data:geo:GSE13507 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ene Prognostic Index Verified by Genome-Wide CRISPR Can Depict the Tumor Microenvironment and Gu", "tematically evaluated. Using the genome-wide CRISPR screening data acquired from DepMap (Cancer", "gov/geo/). More importantly, the genome-wide CRISPR screening results of bladder cancer cell lin"], "order_basis": "paper_text_order:34", "id": "assay:1"}, {"role": "data_generation", "definition_id": "methylation_array", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.85, "evidence": ["RSORT-ABS, QUANTISEQ, MCPCOUNTER, XCELL, and EPIC methods from the TIMER 2.0 database (http://"], "order_basis": "paper_text_order:8498", "id": "assay:2"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The least absolute shrinkage and selection operator (LASSO) method was conducted in the training group to screen the appropriate variables of the above 11 ECSRGs. Following this, the multivariate cox regression of the left variables was performed in the training group to establish a prognostic cell senescence index (PCSI)."], "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. 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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. 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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}}}