{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35875097", "kind": "science-record", "revision": 4, "content_hash": "sha256:192525799711f74b906311e78019f877581ee9f443d4b84eb0025b5994d435b5", "created_at": "2026-11-01T18:14:57Z", "updated_at": "2026-11-01T22:07:07Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Arecoline Is Associated With Inhibition of Cuproptosis and Proliferation of Cancer-Associated Fibroblasts in Oral Squamous Cell Carcinoma: A Potential Mechanism for Tumor Metastasis.", "doi": "10.3389/fonc.2022.925743", "pmid": "35875097", "authors": ["Jinfei Li", "Shuangyi Chen", "Yuxuan Liao", "Hongyi Wang", "Dawei Zhou", "Bo Zhang"], "journal": "Frontiers in oncology", "year": 2022, "abstract": "Background: Metastatic disease remains the primary cause of death in patients with oral squamous cell carcinoma (OSCC), especially those who use betel nut. The different steps of the metastatic cascade rely on reciprocal interactions between cancer cells and the tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs) are regarded as a significant component in the TME of OSCC. However, the precise mechanisms regulating CAFs in OSCC are poorly understood.\nMethods: Thirteen genes related to the arecoline were analyzed to explore the significant ones involved in arecoline-related OSCC metastasis. The GSE139869 (n = 10) and The Cancer Genome Atlas (TCGA)-OSCC data (n = 361) were mined for the identification of the differentially expressed genes. The least absolute shrinkage and selection operator (LASSO) regression was performed to identify the independent prognostic signatures. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to explore the functional enrichment of selected genes, and gene set enrichment analysis of cuproptosis-related genes was completed. Spearman's analysis and Tumor Immune Estimation Resource (TIMER) were used to visualize the correlation between the infiltration of CAFs and the gene expression. The correlation analysis of the cells and different genes, including CAF infiltration and transcripts per million expression, was assessed. The relationship between arecoline and CAFs was confirmed by cell counting kit-8 assay (CCK-8). CancerSEA was searched to identify the single-cell phenotype.\nResult: Arecoline-associated fibrosis-related OSCC differentially expressed genes (AFOC-DEGs), namely, PLAU, IL1A, SPP1, CCL11, TERT, and COL1A2, were screened out and selected from the Gene Expression Omnibus (GEO) database and TCGA database. AFOC-DEGs were highly expressed in OSCC, which led to poor survival of patients. Functional enrichment analysis, protein-protein interaction network construction, and Spearman's correlation analysis all suggested that AFOC-DEGs were closely associated with cuproptosis. Cellular experiments demonstrated that arecoline stimulation could significantly increase the cell viability of CAFs. Single-sample Gene Set Enrichment Analysis (ssGSEA) results showed that GLS and MTF1 were highly expressed when fibroblasts proliferated at high enrichment levels. In addition, analysis of single-cell sequencing results suggested that OSCC cells with high expression of AFOC-DEGs were associated with OSCC metastasis.\nConclusion: We found a close association between arecoline, cuproptosis, and CAFs, which might play an important role in the metastasis of OSCC.", "claims": [{"id": "claim-method", "statement": "To assess the prognostic value of the DEGs from TCGA, the least absolute shrinkage and selection operator (LASSO) regression was conducted using the R package “glmnet” to feature selection, and 10-fold cross-validation was used to narrow down the candidate genes associated with OSCC prognosis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35875097", "locator": "sections[5] \"Evaluation of the Prognostic Value of Differentially Expressed Genes\" paragraph 2", "quote": "To assess the prognostic value of the DEGs from TCGA, the least absolute shrinkage and selection operator (LASSO) regression was conducted using the R package “glmnet” to feature selection, and 10-fold cross-validation was used to narrow down the candidate genes associated with OSCC prognosis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. The datasets [GSE139869, GSE160395, GSE59414 and GSE38227] for this study can be found in the [GEO Database] [www.ncbi.nlm.nih.gov/geo]. The datasets [TCGA-OSCC] for this study can be found in the [TCGA Database] [https://tcga-data.nci.nih.gov/tcga]. The datasets [FAG] for this study can be found in the [FibROAD Database][https://www.fibroad.org/download.php].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35875097", "locator": "sections[23] \"Data Availability Statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. The datasets [GSE139869, GSE160395, GSE59414 and GSE38227] for this study can be found in the [GEO Database] [www.ncbi.nlm.nih.gov/geo]. The datasets [TCGA-OSCC] for this study can be found in the [TCGA Database] [https://tcga-data.nci.nih.gov/tcga]. The datasets [FAG] for this study can be found in the [FibROAD Database][https://www.fibroad.org/download.php]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The six-gene LASSO-Cox prognostic model achieved AUCs above 0.6 for 1-, 3-, and 5-year survival, with a maximum AUC of 0.636.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35875097", "locator": "sections[14] \"Construction of the Prognostic Gene Signature\" paragraph 5", "quote": "Additionally, the ROC curves of the prognosis model for the survival probability at 1, 3, and 5 years are shown in Figure 3F . All the area under the curve (AUC) values were higher than 0.6 with the maximum AUC value reaching 0.636, certifying the satisfying specificity and sensitivity of the prognosis model."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The six-gene LASSO-Cox prognostic model achieved AUCs above 0.6 for 1-, 3-, and 5-year survival, with a maximum AUC of 0.636.", "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:35875097"], "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:GSE139869"], "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:GSE139869"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35875097", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2022.925743", "sha256": "sha256:21514dcfd629b411c82b220cd49b7aa30158f8ca6eaa8891d92746cb37b98eda", "bytes": 62922, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fonc.2022.925743", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9303015", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE139869", "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=GSE139869", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE139869", "version": null, "note": "Publicly available datasets were analyzed in this study. The datasets [GSE139869, GSE160395, GSE59414 and GSE38227] for this study can be found in the [GEO Database] [www.ncbi.nlm.nih.gov/geo]. The datasets [TCGA-OSCC] for this study can be found in the [TCGA Database] [https://tcga-data.nci.nih.gov/tcga]. The datasets [FAG] for this study can be found in the [FibROAD Database][https://www.fibroad.org/download.php].", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. The datasets [GSE139869, GSE160395, GSE59414 and GSE38227] for this study can be found in the [GEO Database] [www.ncbi.nlm.nih.gov/geo]. The datasets [TCGA-OSCC] for this study can be found in the [TCGA Database] [https://tcga-data.nci.nih.gov/tcga]. The datasets [FAG] for this study can be found in the [FibROAD Database][https://www.fibroad.org/download.php].", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM4147965", "GSM4147966", "GSM4147967", "GSM4147968", "GSM4147969", "GSM4147970", "GSM4147971", "GSM4147972", "GSM4147973", "GSM4147974"], "sample_count": 10, "group_sizes": null, "group_sizes_basis": null, "platform": "19612", "taxon": "Homo sapiens", "title": "LncRNA expression profiles in areca nut chewing induced Tongue Squamous Cell Carcinoma (TSCC) and matched paracancerous tissues", "resolution_checked_at": "2026-11-01T18:06:43Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE160395", "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=GSE160395", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE160395", "version": null, "note": "Publicly available datasets were analyzed in this study. The datasets [GSE139869, GSE160395, GSE59414 and GSE38227] for this study can be found in the [GEO Database] [www.ncbi.nlm.nih.gov/geo]. The datasets [TCGA-OSCC] for this study can be found in the [TCGA Database] [https://tcga-data.nci.nih.gov/tcga]. The datasets [FAG] for this study can be found in the [FibROAD Database][https://www.fibroad.org/download.php].", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. The datasets [GSE139869, GSE160395, GSE59414 and GSE38227] for this study can be found in the [GEO Database] [www.ncbi.nlm.nih.gov/geo]. The datasets [TCGA-OSCC] for this study can be found in the [TCGA Database] [https://tcga-data.nci.nih.gov/tcga]. The datasets [FAG] for this study can be found in the [FibROAD Database][https://www.fibroad.org/download.php].", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM4872672", "GSM4872678", "GSM4872681", "GSM4872685", "GSM4872686", "GSM4872687", "GSM4872688", "GSM4872689"], "sample_count": 8, "group_sizes": null, "group_sizes_basis": null, "platform": "21185", "taxon": "Homo sapiens", "title": "Transcriptomic profiling between HSC-3 cells and its highly metastatic subline, HSC-3-M3 cells", "resolution_checked_at": "2026-11-01T18:06:43Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE139869 not downloaded", "asset:data:geo:GSE139869 licence not read", "asset:data:geo:GSE160395 not downloaded", "asset:data:geo:GSE160395 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "group_comparison", "specific": "welch_t_test", "label": "Group comparison", "dsl_operations": ["welch_t"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Welch"}}, {"id": "method-2", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Wilcoxon"}}, {"id": "method-3", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {"hazard_ratio": "e of the p-values ​​for hazard ratio (HR) in the model"}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "Log-rank"}}, {"id": "method-4", "family": "correlation_analysis", "specific": "spearman", "label": "Correlation analysis", "dsl_operations": ["spearman_rho"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.7, "band": "medium", "quote": "Spearman's correlation"}}, {"id": "method-5", "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": 0.7, "band": "medium", "quote": "protein-protein interaction"}}, {"id": "method-6", "family": null, "specific": null, "label": "LASSO regression with 10-fold cross-validation", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "To assess the prognostic value of the DEGs from TCGA, the least absolute shrinkage and selection operator (LASSO) regression was conducted using the R package “glmnet” to feature selection, and 10-fold cross-validation was used to narrow down the candidate genes associated with OSCC prognosis."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["welch_t"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: welch_t_test."}, "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": ["GSE139869", "GSE160395", "GSE59414 and GSE38227"], "resolved_accessions": ["GSE139869", "GSE160395"], "statements": ["Publicly available datasets were analyzed in this study. The datasets [GSE139869, GSE160395, GSE59414 and GSE38227] for this study can be found in the [GEO Database] [www.ncbi.nlm.nih.gov/geo]. The datasets [TCGA-OSCC] for this study can be found in the [TCGA Database] [https://tcga-data.nci.nih.gov/tcga]. The datasets [FAG] for this study can be found in the [FibROAD Database][https://www.fibroad.org/download.php]."], "basis": "The paper names GSE139869, GSE160395 in GEO Database and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["welch_t"], "assets": ["source:pmid:35875097", "data:geo:GSE139869"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE139869"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T17:56:50Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 18093, "completion_tokens": 2482, "cached_tokens": 256}}, "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:35875097", "type": "paper", "label": "pmid:35875097"}, {"id": "source:pmid:35875097", "type": "manuscript", "label": "PMID 35875097 full text"}, {"id": "data:geo:GSE139869", "type": "dataset", "label": "GEO GSE139869"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:35875097", "type": "paper", "label": "pmid:35875097"}, {"id": "source:pmid:35875097", "type": "manuscript", "label": "PMID 35875097 full text"}, {"id": "data:geo:GSE139869", "type": "dataset", "label": "GEO GSE139869"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-35875097", "type": "extraction", "used": ["source:pmid:35875097"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE139869", "type": "accession_resolution", "used": ["data:geo:GSE139869"], "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:35875097", "parent_hash": "sha256:2a5a62bdf2cf99173b505f1f67f112484ca6f41ec58505d076ecb941058ab6fb", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE139869 licence not read", "asset:data:geo:GSE139869 not downloaded", "asset:data:geo:GSE160395 licence not read", "asset:data:geo:GSE160395 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "apoptosis_assay", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["was confirmed by cell counting kit-8 assay (CCK-8). CancerSEA was searched to identify the sin"], "order_basis": "paper_text_order:1654", "id": "assay:1"}, {"role": "analysis", "definition_id": "group_comparison", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["welch_t"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["Welch"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]},"meta":{"api_version":"v1","automation_ladder_snapshot":"ba34b49490d9bfaf","automation_ladder_caveats":["Method extraction is rule-based and has no hand-judged accuracy sample. Evidence bands order textual support; method agreement intervals are null (n=0), never probabilities. Work-type validation does not validate methods.","Operation coverage describes only explicitly named methods. It does not prove a complete protocol, compatible parameters, successful compilation or re-execution. Unrecognised or ambiguous methods require review.","Data reachability is a textual accession or public-data statement. No dataset was downloaded or checked for access, completeness or licence.","Capabilities are planning states seeded from the dated equipment register. No bench ownership, completed quote or partner booking is inferred. Procurement counts are dependencies, not guaranteed replications or financial returns.","Tier and blocker counts are deterministic assessments of this corpus, not measured agreement. R3 is reserved for procurement; unresolved methods and data require human work (R4). The most restrictive axis wins, with capability, method, data as tie-breaks. Resolving one blocker can leave another at the same tier."],"engine":"corpus_engine","engine_provider":"rule_based_v1+lex99e1195c7d6f","run_id":"run-20261023T122449232913","source":"esearch","source_detail":"PubMed mirror biomed_pubmed (read-only)","run_status":"complete","imported_at":"2026-11-03T20:16:52+00:00","generated_at":"2026-11-04T01:23:24+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}}}