{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39111872", "kind": "science-record", "revision": 4, "content_hash": "sha256:a164c7d3a0a528c7f971b08db816d73a867c24aa8aeb19192f2f4f83d1a3ef53", "created_at": "2026-11-01T20:29:12Z", "updated_at": "2026-11-01T22:54:52Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of hub genes and key pathways in arsenic-treated rice (Oryza sativa L.) based on 9 topological analysis methods of CytoHubba.", "doi": "10.1265/ehpm.24-00095", "pmid": "39111872", "authors": ["Zhen Yu", "Rongxuan Wang", "Tian Dai", "Yuan Guo", "Zanxuan Tian", "Yuanyuan Zhu", "Juan Chen", "Yongjian Yu"], "journal": "Environmental health and preventive medicine", "year": 2024, "abstract": "BACKGROUND: Arsenic is a toxic metalloid that can cause acute and chronic adverse health problems. Unfortunately, rice, the primary staple food for more than half of the world's population, is generally regarded as a typical arsenic-accumulating crop plant. Evidence indicates that arsenic stress can influence the growth and development of the rice plant, and lead to high concentrations of arsenic in rice grain. But the underlying mechanisms remain unclear.\nMETHODS: In the present research, the possible molecules and pathways involved in rice roots in response to arsenic stress were explored using bioinformatics methods. Datasets that involving arsenic-treated rice root and the \"study type\" that was restricted to \"Expression profiling by array\" were selected and downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between the arsenic-treated group and the control group were obtained using the online web tool GEO2R. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to investigate the functions of DEGs. The protein-protein interactions (PPI) network and the molecular complex detection algorithm (MCODE) of DEGs were analyzed using STRING and Cystoscope, respectively. Important nodes and hub genes in the PPI network were predicted and explored using the Cytoscape-cytoHubba plug-in.\nRESULTS: Two datasets, GSE25206 and GSE71492, were downloaded from Gene Expression Omnibus (GEO) database. Eighty common DEGs from the two datasets, including sixty-three up-regulated and seventeen down-regulated genes, were then selected. After functional enrichment analysis, these common DEGs were enriched mainly in 10 GO items, including glutathione transferase activity, glutathione metabolic process, toxin catabolic process, and 7 KEGG pathways related to metabolism. After PPI network and MCODE analysis, 49 nodes from the DEGs PPI network were identified, filtering two significant modules. Next, the Cytoscape-cytoHubba plug-in was used to predict important nodes and hub genes. Finally, five genes [Os01g0644000, PRDX6 (Os07g0638400), PRX112 (Os07g0677300), ENO1(Os06g0136600), LOGL9 (Os09g0547500)] were verified and could serve as the best candidates associated with rice root in response to arsenic stress.\nCONCLUSIONS: In summary, we elucidated the potential pathways and genes in rice root in response to arsenic stress through a comprehensive bioinformatics analysis.", "claims": [{"id": "claim-method", "statement": "The online web tool, GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/), is often used to explore the genetic variations between two or more groups of samples based on the GEOquery and Limma R packages [31].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39111872", "locator": "sections[4] \"2.2 Differentially expressed genes identification\" paragraph 2", "quote": "The online web tool, GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/), is often used to explore the genetic variations between two or more groups of samples based on the GEOquery and Limma R packages [31]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The expression profiles datasets used in this study are publicly available at GEO database (https://www.ncbi.nlm.nih.gov/geo/): GSE25206, GSE99083, and GSE71492.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39111872", "locator": "sections[19] \"Availability of data and materials\" paragraph 2", "quote": "The expression profiles datasets used in this study are publicly available at GEO database (https://www.ncbi.nlm.nih.gov/geo/): GSE25206, GSE99083, and GSE71492."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Using GEO2R on the GEO expression profiles GSE25206 and GSE71492, the study identified 80 common differentially expressed genes and nominated five hub genes associated with rice-root responses to arsenic stress.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39111872", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Datasets that involving arsenic-treated rice root and the “study type” that was restricted to “Expression profiling by array” were selected and downloaded from Gene Expression Omnibus (GEO) database."}, {"asset": "source:pmid:39111872", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Differentially expressed genes (DEGs) between the arsenic-treated group and the control group were obtained using the online web tool GEO2R."}, {"asset": "source:pmid:39111872", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Eighty common DEGs from the two datasets, including sixty-three up-regulated and seventeen down-regulated genes, were then selected."}, {"asset": "source:pmid:39111872", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Finally, five genes [Os01g0644000, PRDX6 (Os07g0638400), PRX112 (Os07g0677300), ENO1(Os06g0136600), LOGL9 (Os09g0547500)] were verified and could serve as the best candidates associated with rice root in response to arsenic stress."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Using GEO2R on the GEO expression profiles GSE25206 and GSE71492, the study identified 80 common differentially expressed genes and nominated five hub genes associated with rice-root responses to arsenic stress.", "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:39111872"], "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:GSE25206"], "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:GSE25206"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39111872", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1265/ehpm.24-00095", "sha256": "sha256:7c7f5dbaf607dd0c69841a432f323a01bc15acf06196ed0a672464e0300dd049", "bytes": 28875, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1265/ehpm.24-00095", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11310560", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE25206", "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=GSE25206", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE25206", "version": null, "note": "The expression profiles datasets used in this study are publicly available at GEO database (https://www.ncbi.nlm.nih.gov/geo/): GSE25206, GSE99083, and GSE71492.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The expression profiles datasets used in this study are publicly available at GEO database (https://www.ncbi.nlm.nih.gov/geo/): GSE25206, GSE99083, and GSE71492.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM619236", "GSM619237", "GSM619238", "GSM619239", "GSM619240", "GSM619241", "GSM619242", "GSM619243", "GSM619244", "GSM619245", "GSM619246", "GSM619247", "GSM619248", "GSM619249", "GSM619250"], "sample_count": 15, "group_sizes": null, "group_sizes_basis": null, "platform": "2025", "taxon": "Oryza sativa; Oryza sativa Indica Group", "title": "Transcriptomic shifts in rice roots in response to Cr (VI) stress", "resolution_checked_at": "2026-11-01T20:16:08Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE71492", "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=GSE71492", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE71492", "version": null, "note": "The expression profiles datasets used in this study are publicly available at GEO database (https://www.ncbi.nlm.nih.gov/geo/): GSE25206, GSE99083, and GSE71492.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The expression profiles datasets used in this study are publicly available at GEO database (https://www.ncbi.nlm.nih.gov/geo/): GSE25206, GSE99083, and GSE71492.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1835738", "GSM1835739", "GSM1835740", "GSM1835741", "GSM1835742", "GSM1835743", "GSM1835744", "GSM1835745", "GSM1835746", "GSM1835747", "GSM1835748", "GSM1835749", "GSM1835750", "GSM1835751", "GSM1835752", "GSM1835753"], "sample_count": 16, "group_sizes": null, "group_sizes_basis": null, "platform": "20752", "taxon": "Oryza sativa", "title": "Microarray based differential transcriptomics study to understand arsenic-thiourea interaction in rice.", "resolution_checked_at": "2026-11-01T20:16:08Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE25206 not downloaded", "asset:data:geo:GSE25206 licence not read", "asset:data:geo:GSE71492 not downloaded", "asset:data:geo:GSE71492 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The online web tool, GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/), is often used to explore the genetic variations between two or more groups of samples based on the GEOquery and Limma R packages [31]."}}, {"id": "method-2", "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": "PPI"}}, {"id": "method-3", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "pathway enrichment"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "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": ["GSE25206", "GSE71492"], "resolved_accessions": ["GSE25206", "GSE71492"], "statements": ["The expression profiles datasets used in this study are publicly available at GEO database (https://www.ncbi.nlm.nih.gov/geo/): GSE25206, GSE99083, and GSE71492."], "basis": "The paper names GSE25206, GSE71492 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:39111872", "data:geo:GSE25206"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE25206"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:26:52Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 8316, "completion_tokens": 2135, "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:39111872", "type": "paper", "label": "pmid:39111872"}, {"id": "source:pmid:39111872", "type": "manuscript", "label": "PMID 39111872 full text"}, {"id": "data:geo:GSE25206", "type": "dataset", "label": "GEO GSE25206"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:39111872", "type": "paper", "label": "pmid:39111872"}, {"id": "source:pmid:39111872", "type": "manuscript", "label": "PMID 39111872 full text"}, {"id": "data:geo:GSE25206", "type": "dataset", "label": "GEO GSE25206"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-39111872", "type": "extraction", "used": ["source:pmid:39111872"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE25206", "type": "accession_resolution", "used": ["data:geo:GSE25206"], "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:39111872", "parent_hash": "sha256:1cc4aecb2efeffa5313e0aba65800bd9c6e9118db4cd71fa066b5e353910481d", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE25206 licence not read", "asset:data:geo:GSE25206 not downloaded", "asset:data:geo:GSE71492 licence not read", "asset:data:geo:GSE71492 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The online web tool, GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/), is often used to explore the genetic variations between two or more groups of samples based on the GEOquery and Limma R packages [31]."], "order_basis": "analysis_only", "id": "assay:1"}]},"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":"2026-11-04T02:50:03+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}}}