{"data":{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40918133", "kind": "science-record", "revision": 2, "content_hash": "sha256:16290cdc8ff8c5938b61c18a2ffed2af9b2ac59b8331d4082abc8a84be88cd5b", "created_at": "2026-11-01T10:25:53Z", "updated_at": "2026-11-01T14:01:47Z", "generator": {"name": "corpus-assay-engine", "converter": "sep_to_sci_v1", "source_package_schema": "urn:bntrg:sep:1.0.0"}, "paper": {"state": "partial", "title": "Comprehensive analysis based on the ubiquitination- and deubiquitylation-related genes reveals the function of NEURL3 in esophageal squamous cell carcinoma.", "doi": "10.3389/fimmu.2025.1632090", "pmid": "40918133", "authors": null, "journal": "Frontiers in immunology", "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": 11.0, "unit": "genes", "tolerance": null, "source": "chars 1341-1470 of source sha256 326a3168b5767c30cab61b3cc17c94ff1d439a311c6fbd5eee06421a52c48127"}, "evidence": [{"asset": "source:pmid:40918133", "locator": "chars 1341-1470 of source sha256 326a3168b5767c30cab61b3cc17c94ff1d439a311c6fbd5eee06421a52c48127", "quote": "The URGs and DRGs prognostic signature consisted of 11 genes and exhibited high accuracy in predicting prognosis of ESCC patient."}]}], "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:40918133"], "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:40918133", "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:40918133' does not resolve to a declared asset"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40918133", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2025.1632090", "sha256": "sha256:326a3168b5767c30cab61b3cc17c94ff1d439a311c6fbd5eee06421a52c48127", "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2025.1632090", "version": null, "note": "Source read by the package builder: full_text.", "structure": {"access_state": "full_text"}}, {"id": "asset:table:pmid:40918133:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:472cde3c9e86c0e5daf4e12afb1f54a220584fdd28eeddfbe540718a97a74fee", "bytes": 1410, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[23]/table-wrap[1]#T1", "version": null, "note": "Univariate and multivariate Cox regression analysis of various prognostic factors in ESCC patients.", "structure": {"pmcid": "PMC12408286", "section_index": 23, "section_title": "Construction and validation of a nomogram for ESCC patients", "row_count": 16, "column_count": 7}, "table": {"label": "Table 1", "caption": "Univariate and multivariate Cox regression analysis of various prognostic factors in ESCC patients.", "rows": [["Patient characteristics", "Univariate analysis", "Multivariate analysis"], ["HR", "95%CI", "P", "HR", "95%CI", "P"], ["Gender (Female vs. Male)", "1.210", "0.685-2.138", "0.511", "", "", ""], ["Age (≥66 vs. <66; y)", "2.033", "1.231-3.357", "0.006", "2.079", "1.131-3.818", "0.018"], ["Drinking (Yes vs. No)", "1.053", "0.656-1.689", "0.831", "", "", ""], ["Smoking (Yes vs. No)", "0.859", "0.532-1.387", "0.534", "", "", ""], ["TNM stage (III-IV vs. I-II)", "2.188", "1.338-3.579", "0.002", "1.915", "1.065-3.443", "0.030"], ["Tumor location (Middle vs. Lower)", "0.724", "0.350-1.497", "0.384", "", "", ""], ["Tumor location (Upper vs. Lower)", "0.643", "0.329-1.255", "0.196", "", "", ""], ["Tumor grade (Moderately vs. Well)", "0.734", "0.377-1.428", "0.362", "", "", ""], ["Tumor grade (Poorly vs. Well)", "0.632", "0.374-1.067", "0.086", "", "", ""], ["Arrhythrnia (Yes vs. No)", "1.388", "0.829-2.322", "0.212", "", "", ""], ["Pneumonia (Yes vs. No)", "1.807", "0.865-3.773", "0.115", "", "", ""], ["Anastomotic leak (Yes vs. No)", "1.513", "0.693-3.301", "0.298", "", "", ""], ["Adjuvant therapy (Yes vs. No)", "2.133", "1.043-4.362", "0.038", "", "", ""], ["Risk score (High vs. Low)", "5.147", "3.015-8.787", "<0.001", "5.563", "2.871-10.780", "<0.001"]], "row_count": 16, "column_count": 7, "numeric_cells": 54, "header_rows": 2, "locator": "section[23]/table-wrap[1]#T1"}}], "gaps": ["asset:source:pmid:40918133 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:40918133", "asset:table:pmid:40918133:1"], "steps": ["read_published_estimate"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:40918133"]}, "gaps": ["corpus_record_absent"]}, "review": {"state": "partial", "machine_critique": {"status": "passed", "providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "full-text-reading-v1", "prompt_hash": "dd98846aa6ba823ff7ada3f094e62103e9026e40a6987fcb7171045964053788", "source_hash": "326a3168b5767c30cab61b3cc17c94ff1d439a311c6fbd5eee06421a52c48127", "raw_response_sha256": "sha256:fa05343c57a4fbd8914498524891475aec4aacf6011b1064e17d93cc6b564998", "raw_response_chars": 5670}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "f86b3113b1ceb9dfc26d553603e55ac816dca419fc67d970d4218de410bad4d4", "source_hash": "326a3168b5767c30cab61b3cc17c94ff1d439a311c6fbd5eee06421a52c48127", "raw_response_sha256": "sha256:f875d14e0fa25915b75b42374fc031c2a2ef5cac60a5c4c8153e95ff24e7ddf4", "raw_response_chars": 31651}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "ec1b7187c798c3f3c8ee44e033c43a00786d3324f91030506236b1c799bff2f9", "source_hash": "326a3168b5767c30cab61b3cc17c94ff1d439a311c6fbd5eee06421a52c48127", "raw_response": "{\"parent_value\":11,\"unit\":\"genes\",\"evidence\":\"The URGs and DRGs prognostic signature consisted of 11 genes and exhibited high accuracy in predicting prognosis of ESCC patient.\",\"target_result\":\"The URGs and DRGs prognostic signature consisted of 11 genes.\",\"number_stated\":true}", "reading": {"parent_value": 11, "unit": "genes", "evidence": "The URGs and DRGs prognostic signature consisted of 11 genes and exhibited high accuracy in predicting prognosis of ESCC patient.", "target_result": "The URGs and DRGs prognostic signature consisted of 11 genes.", "number_stated": true, "source_locator": "chars 1341-1470 of source sha256 326a3168b5767c30cab61b3cc17c94ff1d439a311c6fbd5eee06421a52c48127"}, "recorded_at": "2026-10-31T15:33:57.968671+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "7b0ce2167eb09f83bde54ee115ef796c1d8abd699673d02b00b56d83bf7ce630", "source_hash": "326a3168b5767c30cab61b3cc17c94ff1d439a311c6fbd5eee06421a52c48127", "raw_response": "<think>We need answer JSON only. Need identify single numerical result replication registered target headline numerical result paper main finding. Source supplied appears abstract + methods snippets, results snippets, no detailed numeric performance (AUC etc). Need infer what qualifies headline numerical result. Registered target generic \"headline numerical result the paper states for its main finding.\" Could be 11 genes? The paper's main finding prognostic signature consisted of 11 genes, two molecular subtypes, etc. Need determine expected extraction likely asks numerical result from source. We need report headline number only, exact contiguous quote containing number, attribution via wording. Which number is \"headline numerical result\" perhaps 11 genes. Let's parse.\n\nPaper title comprehensive analysis ... main finding nomogram based on 11 URG/DRG signature. Abstract says \"The URGs and DRGs prognostic signature consisted of 11 genes and exhibited high accuracy...\" This is prominent headline numerical result. It may be target. User asks \"find the single numerical result that a replication of the registered target has to reproduce. Report the headline number only: the value the paper itself states for the registered target, not a value you calculated, converted, averaged or reconstructed.\" Registered target is \"the headline numerical result the paper states for its main finding.\" So likely 11 genes. Need quote exact clause. Evidence perhaps \"The URGs and DRGs prognostic signature consisted of 11 genes and exhibited high accuracy in predicting prognosis of ESCC patient.\" Unit \"genes\". parent_value 11. target_result likely \"The prognostic signature consisted of 11 genes.\" number_stated true.\n\nBut maybe headline numerical result is number of immune cell types 28? Main finding perhaps 28 immune cell types? Yet article abstract headline has no metric except 11 genes. The \"registered target\" perhaps hidden context asks one numerical result. We need only source. Could be C2 subtype survival, but no numerical value in supplied text. Thus 11 is only headline result. Need ensure exact quote contiguous and whole clause for attribution. JSON string.\n\nCould answer:\n{\n\"parent_value\":11,\n\"unit\":\"genes\",\n\"evidence\":\"The URGs and DRGs prognostic signature consisted of 11 genes and exhibited high accuracy in predicting prognosis of ESCC patient.\",\n\"target_result\":\"The URGs and DRGs prognostic signature consisted of 11 genes.\",\n\"number_stated\":true\n}\nNeed no extra. Is unit perhaps \"genes\" as paper prints. It prints \"11 genes\", yes.\n\nLet's ensure \"headline number only\" means parent_value and unit, evidence still whole clause. target_result perhaps concise. Fine.</think>\n\n{\"parent_value\":11,\"unit\":\"genes\",\"evidence\":\"The URGs and DRGs prognostic signature consisted of 11 genes and exhibited high accuracy in predicting prognosis of ESCC patient.\",\"target_result\":\"The URGs and DRGs prognostic signature consisted of 11 genes.\",\"number_stated\":true}", "reading": {"parent_value": 11, "unit": "genes", "evidence": "The URGs and DRGs prognostic signature consisted of 11 genes and exhibited high accuracy in predicting prognosis of ESCC patient.", "target_result": "The URGs and DRGs prognostic signature consisted of 11 genes.", "number_stated": true, "source_locator": "chars 1341-1470 of source sha256 326a3168b5767c30cab61b3cc17c94ff1d439a311c6fbd5eee06421a52c48127"}, "recorded_at": "2026-10-31T15:34:01.406184+00:00"}], "agreement": true, "disagreements": {"physical_methods": {"minimax": ["Loss-of-function studies", "In vitro ESCC cell proliferation assay", "In vitro ESCC cell motility assay"], "minimax_alt": ["Loss-of-function studies", "NEURL3 knockdown in ESCC cells"], "decisive": false}, "analysis_methods": {"minimax": ["Differential expression analysis", "Prognostic gene analysis", "Prognostic signature construction", "Unsupervised clustering analysis", "Gene Ontology enrichment analysis", "Disease Ontology enrichment analysis", "KEGG pathway enrichment analysis", "Single-sample gene set enrichment analysis (ssGSEA)", "Spearman correlation analysis", "TIMER analysis", "CIBERSORT-ABS analysis", "QUANTISEQ analysis", "EPIC analysis", "MCPCOUNTER analysis", "CIBERSORT analysis", "XCELL analysis", "oncoPredict drug-sensitivity analysis", "Molecular docking using AMDock", "Nomogram construction"], "minimax_alt": ["Unsupervised clustering analysis", "Gene Ontology (GO) functional enrichment analysis", "Disease Ontology (DO) and KEGG analysis using the BioEnricher R package", "Single-sample gene set enrichment analysis (ssGSEA)", "Spearman correlation analysis", "TIMER, CIBERSORT-ABS, QUANTISEQ, EPIC, MCPCOUNTER, CIBERSORT, and XCELL algorithms using the IOBR R package", "oncoPredict R package for drug-sensitivity assessment", "Molecular docking using AMDock software", "Nomogram construction combining the URGs and DRGs prognostic signature with clinical characteristics"], "decisive": false}}, "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": "passed", "reason": "The independent readings are incomplete or disagree; the source evidence must resolve the difference.", "evidence": {"provider_errors": []}}, {"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.passed"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "package:7f0e48fd3c0aa9598e84be8fb21485fb570fbab731df716ed9cefd16441e97c7", "type": "sep_package", "label": "SEP v1 package for pmid:40918133"}], "activities": [{"id": "activity:conversion:pmid:40918133", "type": "conversion", "used": ["package:7f0e48fd3c0aa9598e84be8fb21485fb570fbab731df716ed9cefd16441e97c7"], "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:40918133", "parent_hash": "sha256:f3abf5caa441a82db1e2d1c7216a7811a8ce6d2b828e4267aa47c7ba2187d19d", "fork_of": null, "generation": 2}, "gaps": ["abstract", "asset:source:pmid:40918133 not verified", "authors", "capability", "corpus_record_absent", "execution.not_run", "method", "review.human_critique", "review.machine_critique.passed", "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:40918133' 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":"2026-11-04T03:07:00+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}}}