{"data":{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40016772", "kind": "science-record", "revision": 1, "content_hash": "sha256:14183710cacc4afe4779993af3868c50bf37d1acdaac2b74c51a03d863215908", "created_at": "2026-11-01T10:25:49Z", "updated_at": "2026-11-01T10:25:49Z", "generator": {"name": "corpus-assay-engine", "converter": "sep_to_sci_v1", "source_package_schema": "urn:bntrg:sep:1.0.0"}, "paper": {"state": "partial", "title": "A novel stemness-related lncRNA signature predicts prognosis, immune infiltration and drug sensitivity of clear cell renal cell carcinoma.", "doi": "10.1186/s12967-025-06251-6", "pmid": "40016772", "authors": null, "journal": "Journal of translational medicine", "year": 2025, "abstract": null, "claims": [{"id": "claim-1", "statement": "the headline numerical result the paper states for its main finding", "kind": "quantitative", "state": "complete", "target": {"value": 6.0, "unit": "srlncrnas", "tolerance": null, "source": "chars 2117-2179 of source sha256 03026cbe679b4a1f7eb958185e9d13783ffd626c7e0277a99bf21fd7fc123f39"}, "evidence": [{"asset": "source:pmid:40016772", "locator": "chars 2117-2179 of source sha256 03026cbe679b4a1f7eb958185e9d13783ffd626c7e0277a99bf21fd7fc123f39", "quote": "Six SRlncRNAs were used to construct the prognostic signature."}]}], "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:40016772"], "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:40016772", "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:40016772' does not resolve to a declared asset"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40016772", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12967-025-06251-6", "sha256": "sha256:03026cbe679b4a1f7eb958185e9d13783ffd626c7e0277a99bf21fd7fc123f39", "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12967-025-06251-6", "version": null, "note": "Source read by the package builder: full_text.", "structure": {"access_state": "full_text"}}], "gaps": ["asset:source:pmid:40016772 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:40016772"], "steps": ["read_published_estimate"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:40016772"]}, "gaps": ["corpus_record_absent"]}, "review": {"state": "partial", "machine_critique": {"status": "blocked", "providers": [{"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "3060074df26371c8eabf61fd4ab39d366740588ffd4bc4f2a808cb6d3906140d", "source_hash": "03026cbe679b4a1f7eb958185e9d13783ffd626c7e0277a99bf21fd7fc123f39", "raw_response_sha256": "sha256:d51da2192d2a2e6da4c32bf70f8cc48a6565aa6676b367c5e020891e76f10831", "raw_response_chars": 54477}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "775adb2bdebb8c6c3c5b4d7377453bbcd7bca8ac784bff75cfebebeb9e4da684", "source_hash": "03026cbe679b4a1f7eb958185e9d13783ffd626c7e0277a99bf21fd7fc123f39", "raw_response": "{\"parent_value\":6,\"unit\":\"SRlncRNAs\",\"evidence\":\"Six SRlncRNAs were used to construct the prognostic signature.\",\"target_result\":\"The paper states that six SRlncRNAs were used to construct the prognostic signature.\",\"number_stated\":true}", "reading": {"parent_value": 6, "unit": "SRlncRNAs", "evidence": "Six SRlncRNAs were used to construct the prognostic signature.", "target_result": "The paper states that six SRlncRNAs were used to construct the prognostic signature.", "number_stated": true, "source_locator": "chars 2117-2179 of source sha256 03026cbe679b4a1f7eb958185e9d13783ffd626c7e0277a99bf21fd7fc123f39"}, "recorded_at": "2026-10-31T15:31:51.563582+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "45e2805271f290ff2287e6ab50ebbd62d43c09865ce986f7bc2382d60f20b5e6", "source_hash": "03026cbe679b4a1f7eb958185e9d13783ffd626c7e0277a99bf21fd7fc123f39", "raw_response": "<think>We need answer JSON only, claims from source. Need identify single numerical result headline main finding registered target. Source has six SRlncRNAs signature, perhaps number stated is Six. Need determine \"headline numerical result paper states for its main finding\", likely signature comprised of 6 SRlncRNAs. The question expects extraction. Need exact contiguous quote containing number and attribution. Sentence: \"Six SRlncRNAs were used to construct the prognostic signature.\" Headline numerical result maybe six lncRNAs. Need parent_value number 6, unit perhaps \"SRlncRNAs\" (paper prints? It doesn't print \"6 SRlncRNAs\", but \"Six SRlncRNAs\"). Unit must be unit paper prints. Could use \"SRlncRNAs\". Evidence exact quote. target_result perhaps \"Six SRlncRNAs were used to construct the prognostic signature.\" number_stated true.\n\nBut need inspect wording: Registered target = \"the headline numerical result the paper states for its main finding.\" Main finding is novel stemness-related lncRNA signature. Numerical result in supplied source: Six SRlncRNAs used. Also 787 DEGs etc ancillary. The single headline likely six. Need report headline number only perhaps target_result should concise result perhaps \"Six SRlncRNAs were used to construct the prognostic signature.\" They demand \"Report headline number only\" but schema target_result string. Perhaps set target_result \"Six SRlncRNAs\". Evidence full clause. unit \"SRlncRNAs\". Ensure exact quote. Parent value 6.\n\nCould there be actual headline result elsewhere omitted? Source appears abstract/results but detailed signature results absent. The numerical result likely number of genes (six). Need not overthink. Output valid JSON no markdown.</think>\n\n{\"parent_value\":6,\"unit\":\"SRlncRNAs\",\"evidence\":\"Six SRlncRNAs were used to construct the prognostic signature.\",\"target_result\":\"Six SRlncRNAs were used to construct the prognostic signature.\",\"number_stated\":true}", "reading": {"parent_value": 6, "unit": "SRlncRNAs", "evidence": "Six SRlncRNAs were used to construct the prognostic signature.", "target_result": "Six SRlncRNAs were used to construct the prognostic signature.", "number_stated": true, "source_locator": "chars 2117-2179 of source sha256 03026cbe679b4a1f7eb958185e9d13783ffd626c7e0277a99bf21fd7fc123f39"}, "recorded_at": "2026-10-31T15:31:52.861157+00:00"}], "agreement": false, "disagreements": [], "agreement_basis": {"policy": "decisive_fields", "decisive_fields": ["work_type", "number_stated", "parent_value", "unit"]}, "blinded": true}, "human_critique": {"status": "not_run", "reviewer": null, "signed_at": null, "conflict_checked": false, "commentary": null}, "stages": [{"key": "target_materials", "status": "pending", "reason": null, "evidence": null}, {"key": "independent_readings", "status": "blocked", "reason": "The independent readings are incomplete or disagree; the source evidence must resolve the difference.", "evidence": {"provider_errors": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "reason": "a repository quotation is absent from the supplied text", "raw_response": "{\n  \"target_result\": \"Six SRlncRNAs were used to construct the prognostic signature.\",\n  \"work_type\": \"analysis_plus_physical_validation\",\n  \"physical_methods\": [\n    \"single-cell RNA-seq (scRNA-seq)\",\n    \"RT-qPCR\",\n    \"in vitro experiments\",\n    \"in vivo experiments\"\n  ],\n  \"analysis_methods\": [\n    \"RNA stemness scores (RNAss)\",\n    \"weighted correlation network analysis (WGCNA)\",\n    \"least absolute shrinkage and selection operator (LASSO)\",\n    \"multivariate Cox regression\",\n    \"gene set enrichment analysis (GSEA)\",\n    \"immune infiltration assessment\",\n    \"drug sensitivity prediction\",\n    \"mutation landscape analysis\",\n    \"Student's t-test\",\n    \"Mann–Whitney U test\",\n    \"limma\"\n  ],\n  \"statistical_method\": \"The least absolute shrinkage and selection operator (LASSO) in combination with multivariate Cox regression was selected as the optimal approach.\",\n  \"method_evidence\": \"The least absolute shrinkage and selection operator (LASSO) in combination with multivariate Cox regression was selected as the optimal approach.\",\n  \"repositories\": [\n    {\n      \"repository\": \"The Cancer Genome Atlas (TCGA)\",\n      \"accession\": \"TCGA-KIRC\",\n      \"data_description\": \"Gene-expression and clinical data for the TCGA-KIRC training cohort, which was used to construct and assess the prognostic signature.\",\n      \"evidence\": \"Gene-expression and clinical data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Samples from TCGA-KIRC and GSE29609 cohorts were designated as the training and validation cohorts, respectively.\",\n      \"publicly_downloadable\": true\n    },\n    {\n      \"repository\": \"Gene Expression Omnibus (GEO)\",\n      \"accession\": \"GSE29609\",\n      \"data_description\": \"Gene-expression and clinical data for the GSE29609 validation cohort, which was used to validate the prognostic signature.\",\n      \"evidence\": \"Gene-expression and clinical data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Samples from TCGA-KIRC and GSE29609 cohorts were designated as the training and validation cohorts, respectively.\",\n      \"publicly_downloadable\": true\n    }\n  ],\n  \"availability_statement\": \"The original data presented in this study are included within the article or its accompanying Supplementary Materials. Essential scripts and codes used for analysis are available on the Github website (https://github.com/pengdubjcancer/kirc_SRlncRNAs). For any further inquiries, please feel free to contact the corresponding author.\",\n  \"data_on_request\": true,\n  \"source_claims\": [\n    \"The study developed a prognostic signature consisting of six SRlncRNAs.\",\n    \"LASSO combined with multivariate Cox regression was selected as the optimal modeling approach.\",\n    \"TCGA-KIRC and GSE29609 were designated as the training and validation cohorts, respectively.\",\n    \"The paper reports in vitro and in vivo validation of the findings.\"\n  ],\n  \"missing_information\": [\n    \"The supplied text does not state a quantitative performance result for the prognostic signature, such as a hazard ratio, concordance index, AUC, or survival difference.\",\n    \"The names of all six SRlncRNAs in the signature are not provided; only EMX2OS and LINC00944 are explicitly discussed.\",\n    \"The regression coefficients and risk-score formula for the six-SRlncRNA signature are not provided.\",\n    \"The paper does not explicitly state that TCGA-KIRC or GSE29609 can be accessed without an application, embargo, or request; public availability is inferred only from the statement that the data were downloaded from the named databases.\",\n    \"The numerical criteria used to identify the signature's six SRlncRNAs are not reported in the supplied text.\"\n  ],\n  \"evidence_spans\": [\n    \"Six SRlncRNAs were used to construct the prognostic signature.\",\n    \"The least absolute shrinkage and selection operator (LASSO) in combination with multivariate Cox regression was selected as the optimal approach.\",\n    \"Gene-expression and clinical data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases.\",\n    \"Samples from TCGA-KIRC and GSE29609 cohorts were designated as the training and validation cohorts, respectively.\",\n    \"Expression and effects of SRlncRNAs in ccRCC were further corroborated through the utilization of single-cell RNA-seq (scRNA-seq), as well as in vitro and in vivo experiments.\",\n    \"ScRNA-seq and RT-qPCR demonstrated the differential expression of SRlncRNAs between ccRCC tumors and normal tissues.\",\n    \"In vitro and in vivo experiments demonstrated that downregulation of EMX2OS and LINC00944 affected the proliferation, migration, invasion, apoptosis, and metastasis of ccRCC cells.\",\n    \"The original data presented in this study are included within the article or its accompanying Supplementary Materials. Essential scripts and codes used for analysis are available on the Github website (https://github.com/pengdubjcancer/kirc_SRlncRNAs). For any further inquiries, please feel free to contact the corresponding author.\"\n  ]\n}"}]}}, {"key": "source_resolution", "status": "pending", "reason": null, "evidence": null}, {"key": "protocol_reconstruction", "status": "pending", "reason": null, "evidence": null}, {"key": "control_execution", "status": "pending", "reason": null, "evidence": null}, {"key": "control_comparison", "status": "pending", "reason": null, "evidence": null}, {"key": "publication", "status": "pending", "reason": null, "evidence": null}], "gaps": ["review.human_critique", "review.machine_critique.blocked"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "package:53c07dd8eccc1336442a84e59b71fd88ecb6191cec853cb3e27939e0d7adf44c", "type": "sep_package", "label": "SEP v1 package for pmid:40016772"}], "activities": [{"id": "activity:conversion:pmid:40016772", "type": "conversion", "used": ["package:53c07dd8eccc1336442a84e59b71fd88ecb6191cec853cb3e27939e0d7adf44c"], "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": "f3e8e2b9-6830-4a8d-a26a-00846e8574dc", "parent_hash": "53c07dd8eccc1336442a84e59b71fd88ecb6191cec853cb3e27939e0d7adf44c", "fork_of": null, "generation": 1}, "gaps": ["abstract", "asset:source:pmid:40016772 not verified", "authors", "capability", "corpus_record_absent", "execution.not_run", "method", "review.human_critique", "review.machine_critique.blocked", "step:obtain_source_data blocked on data:not_downloaded", "step:run_analysis blocked on no owned computational capability is bound to this experiment", "step:run_analysis input 'materials:the source data behind the published result in pmid:40016772' 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":"2026-11-04T03:45:33+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}}}