{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:29290775", "kind": "science-record", "revision": 7, "content_hash": "sha256:6d4450f1ffda43504f80a7a5ac48a4b5c41ddae18f75658a70df64e0449decff", "created_at": "2026-11-01T15:40:30Z", "updated_at": "2026-11-01T22:43:13Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Nuclear EGFR and Integrator/Super Elongation Complex concurrently binds to Immediate Early Genes for gene transactivation.", "doi": "10.7150/jca.21925", "pmid": "29290775", "authors": ["Victor Chun-Lam Wong"], "journal": "Journal of Cancer", "year": 2018, "abstract": "The gene transactivation function of nuclear EGFR (nEGFR) has been studied by investigating the genomic co-occupancies of nEGFR and RNA Polymerase II (RNAPII). However, due to RNAPII pausing, the co-recruitment of RNAPII and nEGFR does not necessarily represent productive transactivation. In this study, we integrated gatekeepers of productive transcriptional elongation such as Integrator and Super Elongation Complex (SEC) to interrogate the function of nEGFR. By analyzing publicly available ChIP-seq and RNA-seq data, we aims to 1) explore the function of nEGFR, 2) unravel nEGFR target genes, and 3) discuss potential mechanisms of nEGFR chromatin recruitment. EGF treatment in HeLa cells instigated chromatin recruitment of nEGFR, ERK, RNAPII, Integrator, and SEC in a cluster of 61 EGF-responsive genes. The function of nEGFR was identified as gene-activating rather than gene-repressing. Within the cluster of EGF-responsive genes, nEGFR targeted eleven Immediate Early Genes (IEGs) - JUN, EGR1, JUNB, IER2, KLF2, FOS, FOSL1, RHOB, CCNL1, DUSP2, and DUSP5, which up-regulated >2-fold after EGF stimulation. The promoter of these target genes commonly harbors AT-rich minimal consensus sequences for nEGFR binding. In addition, TCGA data analysis demonstrated positive correlations between EGFR and JUN/FOSL1/RHOB expressions, as well as clinical correlations in specific cancer types. To our knowledge, this is the first study to compare the genome-wide distribution of nEGFR versus Integrator and SEC, providing novel insight into supporting the gene-activating function of nEGFR. We revealed a panel of eleven nEGFR target genes, which concurrently recruited nEGFR, RNAPII, Integrator, and SEC for productive transcriptional elongation.", "claims": [{"id": "claim-method", "statement": "For evaluating the Pearson's correlation coefficient between EGFR and IEG expressions, TCGA RNA-seq data with EGF mRNA expressions above average was subjected to analysis and visualized by ComplexHeatmap package in R. Kaplan-Meier (KM) survival curve analysis and Cox proportional hazards analysis were performed and visualized using survminer and survival package in R.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29290775", "locator": "sections[7] \"TCGA RNA-seq and survival data analyses\" paragraph 2", "quote": "For evaluating the Pearson's correlation coefficient between EGFR and IEG expressions, TCGA RNA-seq data with EGF mRNA expressions above average was subjected to analysis and visualized by ComplexHeatmap package in R. Kaplan-Meier (KM) survival curve analysis and Cox proportional hazards analysis were performed and visualized using survminer and survival package in R."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Collections of dataset were downloaded from Gene Expression Omnibus (GEO) database repository (Table S1).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29290775", "locator": "sections[3] \"Data acquisition, sequencing data mapping, and data processing\" paragraph 2", "quote": "Collections of dataset were downloaded from Gene Expression Omnibus (GEO) database repository (Table S1)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study found that “The function of nEGFR was identified as gene-activating rather than gene-repressing,” and its clinical analyses used Pearson correlation, Kaplan–Meier, and Cox proportional hazards methods on TCGA RNA-seq and survival data downloaded through cBioPortal and processed in R.", "kind": "quantitative", "target": {"value": 0.35, "unit": "correlation coefficient", "tolerance": null, "source": "The expressions of JUN, FOSL1, and RHOB exhibited significant and positive correlations with EGFR in bladder, head and neck, and renal cell carcinoma, respectively (Pearson's r = 0.35 - 0.41; p < 0.05). Their expressions were significantly associated with overall survival of patients in KM analysis (log-rank p=0.0001-0.0075) and were identified as independent prognostic markers by multivariate Cox regression analysis."}, "evidence": [{"asset": "source:pmid:29290775", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The function of nEGFR was identified as gene-activating rather than gene-repressing."}, {"asset": "source:pmid:29290775", "locator": "sections[7] \"TCGA RNA-seq and survival data analyses\" paragraph 2", "quote": "TCGA RNA expression data (RNA Seq V2 RSEM) and survival data were queried and downloaded via cBioPortal (http://www.cbioportal.org/), followed by data processing in R environment."}, {"asset": "source:pmid:29290775", "locator": "sections[7] \"TCGA RNA-seq and survival data analyses\" paragraph 2", "quote": "For evaluating the Pearson's correlation coefficient between EGFR and IEG expressions, TCGA RNA-seq data with EGF mRNA expressions above average was subjected to analysis and visualized by ComplexHeatmap package in R. Kaplan-Meier (KM) survival curve analysis and Cox proportional hazards analysis were performed and visualized using survminer and survival package in R."}, {"asset": "source:pmid:29290775", "locator": "sections[14] \"TCGA RNA-seq and survival data analyses\" paragraph 2", "quote": "The expressions of JUN, FOSL1, and RHOB exhibited significant and positive correlations with EGFR in bladder, head and neck, and renal cell carcinoma, respectively (Pearson's r = 0.35 - 0.41; p < 0.05). Their expressions were significantly associated with overall survival of patients in KM analysis (log-rank p=0.0001-0.0075) and were identified as independent prognostic markers by multivariate Cox regression analysis."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The study found that “The function of nEGFR was identified as gene-activating rather than gene-repressing,” and its clinical analyses used Pearson correlation, Kaplan–Meier, and Cox proportional hazards methods on TCGA RNA-seq and survival data downloaded through cBioPortal and processed in R.", "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:29290775"], "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": "blocked", "blocked_on": "data:accession_absent", "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": [], "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": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:29290775", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.7150/jca.21925", "sha256": "sha256:334a1883fb20c97fd0a6a689d1c415240b841ada65cd1741a74721263070b9d4", "bytes": 30853, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.7150/jca.21925", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC5743717", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}], "gaps": []}, "analysis": {"state": "complete", "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": 1.0, "band": "verbatim", "quote": "For evaluating the Pearson's correlation coefficient between EGFR and IEG expressions, TCGA RNA-seq data with EGF mRNA expressions above average was subjected to analysis and visualized by ComplexHeatmap package in R. Kaplan-Meier (KM) survival curve analysis and Cox proportional hazards analysis were performed and visualized using survminer and survival package in R."}}, {"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": 0.8, "band": "high", "quote": "Cox proportional hazards"}}, {"id": "method-3", "family": "correlation_analysis", "specific": "pearson", "label": "Correlation analysis", "dsl_operations": ["pearson_r"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.8, "band": "high", "quote": "Pearson's correlation"}}], "targets": [{"id": "target-published-estimate", "claim_id": "claim-target-result", "operation": "cox_ph", "expected_value": 0.35, "unit": "correlation coefficient", "tolerance": null, "state": "complete", "note": "The published estimate as the reader quoted it from the paper. No tolerance is published because the paper states none."}], "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": "blocked", "tier": "R4", "blocking_axis": "data", "blocked_on": "data:accession_absent", "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": "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": "R4", "reachable": false, "accessions": [], "resolved_accessions": [], "statements": ["Collections of dataset were downloaded from Gene Expression Omnibus (GEO) database repository (Table S1)."], "basis": "The paper names no accession to its source data, so the data has to come from the authors."}}, "can_run": {"dsl_operations": ["survival_km"], "assets": ["source:pmid:29290775"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:None"]}, "gaps": ["data:accession_absent"]}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:33:22Z", "independence": "same_provider"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 8, "usage": {"prompt_tokens": 66005, "completion_tokens": 4749, "cached_tokens": 17432}}, "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:29290775", "type": "paper", "label": "pmid:29290775"}, {"id": "source:pmid:29290775", "type": "manuscript", "label": "PMID 29290775 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:29290775", "type": "paper", "label": "pmid:29290775"}, {"id": "source:pmid:29290775", "type": "manuscript", "label": "PMID 29290775 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-29290775", "type": "extraction", "used": ["source:pmid:29290775"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-None", "type": "accession_resolution", "used": ["data:geo:None"], "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:29290775", "parent_hash": "sha256:a080a21100c82e30fd6ea29522e57050b6161429d31ef0ac76a58bde785c26a0", "fork_of": null, "generation": 6}, "gaps": ["execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique", "step:obtain_source_data blocked on data:accession_absent"], "assays": [{"role": "data_generation", "definition_id": "chip_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["on of nEGFR. By analyzing publicly available ChIP-seq and RNA-seq data, we aims to 1) explore the", "tudy analyzed publicly available RNA-seq and ChIP-seq data that shared the same experimental condi", "database repository (Table S1). RNA-seq and ChIP-seq data shared the same experimental condition—", "transcripts was estimated by Cuffdiff 9. For ChIP-seq data, bowtie2 was used for mapping the ChIP-"], "order_basis": "paper_text_order:574", "id": "assay:1"}, {"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["By analyzing publicly available ChIP-seq and RNA-seq data, we aims to 1) explore the function of", "lling This study analyzed publicly available RNA-seq and ChIP-seq data that shared the same exper", "mnibus (GEO) database repository (Table S1). RNA-seq and ChIP-seq data shared the same experiment", "ml) for 20 min after 48 hr serum starvation. RNA-seq data was aligned to the human genome hg19 us"], "order_basis": "paper_text_order:587", "id": "assay:2"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["EGFR chromatin recruitment. EGF treatment in HeLa cells instigated chromatin recruitment of nE", "data shared the same experimental condition—HeLa cells were treated with EGF (100 ng/ml) for", "same experimental condition — serum-starved HeLa cells treated with 100 ng/ml EGF for 20 min.", "cells treated with 100 ng/ml EGF for 20 min. HeLa cells provide an experimental model to study"], "order_basis": "paper_text_order:762", "id": "assay:3"}, {"role": "data_generation", "definition_id": "clinical_trial", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["R proteins 12. Serum-starved HeLa cells were treated with or without EGF for 20 min to study the differential gen"], "order_basis": "paper_text_order:3183", "id": "assay:4"}, {"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": 1.0, "evidence": ["For evaluating the Pearson's correlation coefficient between EGFR and IEG expressions, TCGA RNA-seq data with EGF mRNA expressions above average was subjected to analysis and visualized by ComplexHeatmap package in R. Kaplan-Meier (KM) survival curve analysis and Cox proportional hazards analysis were performed and visualized using survminer and survival package in R."], "order_basis": "consumes_earlier_output", "id": "assay:5"}]},"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":"2026-11-04T00:35:43+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}}}