{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38645867", "kind": "science-record", "revision": 4, "content_hash": "sha256:65bf61109dfaccaa67c313d905fcba5352e43587bee398ade2b538e5f38200c0", "created_at": "2026-11-01T19:20:37Z", "updated_at": "2026-11-01T22:11:43Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "[Screening for Characteristic Genes of Different Traditional Chinese Medicine Syndromes of Psoriasis Vulgaris: A Study Based on Bioinformatics and Machine Learning].", "doi": "10.12182/20240360402", "pmid": "38645867", "authors": ["Xuewei Liu", "Huangchao Jia", "Liyun Wang", "Ziwen Wang", "Mengyue Xu", "Yunfei Li", "Ronghui Wang"], "journal": "Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition", "year": 2024, "abstract": "Objective: To screen for the key characteristic genes of the psoriasis vulgaris (PV) patients with different Traditional Chinese Medicine (TCM) syndromes, including blood-heat syndrome (BHS), blood stasis syndrome (BSS), and blood-dryness syndrome (BDS), through bioinformatics and machine learning and to provide a scientific basis for the clinical diagnosis and treatment of PV of different TCM syndrome types.\nMethods: The GSE192867 dataset was downloaded from Gene Expression Omnibus (GEO). The limma package was used to screen for the differentially expressed genes (DEGs) of PV, BHS, BSS, and BDS in PV patients and healthy populations. In addition, KEGG (Kyoto Encyclopedia of Genes and Genes) pathway enrichment analysis was performed. The DEGs associated with PV, BHS, BSS, and BDS were identified in the screening and were intersected separately to obtain differentially characterized genes. Out of two algorithms, the support vector machine (SVM) and random forest (RF), the one that produced the optimal performance was used to analyze the characteristic genes and the top 5 genes were identified as the key characteristic genes. The receiver operating characteristic (ROC) curves of the key characteristic genes were plotted by using the pROC package, the area under curve (AUC) was calculated, and the diagnostic performance was evaluated, accordingly.\nResults: The numbers of DEGs associated with PV, BHS, BSS, and BDS were 7699, 7291, 7654, and 6578, respectively. KEGG enrichment analysis was focused on Janus kinase (JAK)/signal transducer and activator of transcription (STAT), cyclic adenosine monophosphate (cAMP), mitogen-activated protein kinase (MAPK), apoptosis, and other pathways. A total of 13 key characteristic genes were identified in the screening by machine learning. Among the 13 key characteristic genes, malectin (MLEC), TUB like protein 3 (TULP3), SET domain containing 9 (SETD9), nuclear envelope integral membrane protein 2 (NEMP2), and BTG anti-proliferation factor 3 (BTG3) were the key characteristic genes of BHS; phosphatase 15 (DUSP15), C1q and tumor necrosis factor related protein 7 (C1QTNF7), solute carrier family 12 member 5 (SLC12A5), tripartite motif containing 63 (TRIM63), and ubiquitin associated protein 1 like (UBAP1L) were the key characteristic genes of BSS; recombinant mouse protein (RRNAD1), GTPase-activating protein ASAP3 Protein (ASAP3), and human myomesin 2 (MYOM2) were the key characteristic genes of BDS. Moreover, all of them showed high diagnostic efficacy.\nConclusion: There are significant differences in the characteristic genes of different PV syndromes and they may be potential biomarkers for diagnosing TCM syndromes of PV.", "claims": [{"id": "claim-method", "statement": "利用limma包分别对“PV.txt”、“BHS.txt”、“BSS.txt”和“BDS.txt”文件进行差异分析[10]。以|log2(fold change, FC)|>3，P<0.05为标准筛选差异表达基因（differentially expressed genes, DEGs），并绘制火山图。", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38645867", "locator": "sections[5] \"筛选差异表达基因\" paragraph 2", "quote": "利用limma包分别对“PV.txt”、“BHS.txt”、“BSS.txt”和“BDS.txt”文件进行差异分析[10]。以|log2(fold change, FC)|>3，P<0.05为标准筛选差异表达基因（differentially expressed genes, DEGs），并绘制火山图。"}], "state": "complete"}, {"id": "claim-data-access", "statement": "通过GEO数据库（http://www.ncbi. nlm.nih.gov/geo/）下载GSE192867数据集。该数据集中有10例来自健康人群，有62例PV患者（其中BHS患者16例、BSS患者23例、BDS患者23例）。在数据集中，用Affymetrix Human Clariom D Assay检测健康人群和PV患者外周血单核细胞转录组的表达。", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38645867", "locator": "sections[4] \"数据来源与预处理\" paragraph 2", "quote": "通过GEO数据库（http://www.ncbi. nlm.nih.gov/geo/）下载GSE192867数据集。该数据集中有10例来自健康人群，有62例PV患者（其中BHS患者16例、BSS患者23例、BDS患者23例）。在数据集中，用Affymetrix Human Clariom D Assay检测健康人群和PV患者外周血单核细胞转录组的表达。"}], "state": "complete"}, {"id": "claim-target-result", "statement": "差异分析结果显示，“PV.txt”共筛选出7699个与PV相关的DEGs（图1A）；“BHS.txt”共筛选出7291个与BHS相关的DEGs（图1B）；“BSS.txt”共筛选出7654个与BSS相关的DEGs（图1C）；“BDS.txt”共筛选出6578个与BDS相关的DEGs（图1D）。", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38645867", "locator": "sections[11] \"DEGs的筛选\" paragraph 2", "quote": "差异分析结果显示，“PV.txt”共筛选出7699个与PV相关的DEGs（图1A）；“BHS.txt”共筛选出7291个与BHS相关的DEGs（图1B）；“BSS.txt”共筛选出7654个与BSS相关的DEGs（图1C）；“BDS.txt”共筛选出6578个与BDS相关的DEGs（图1D）。"}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "差异分析结果显示，“PV.txt”共筛选出7699个与PV相关的DEGs（图1A）；“BHS.txt”共筛选出7291个与BHS相关的DEGs（图1B）；“BSS.txt”共筛选出7654个与BSS相关的DEGs（图1C）；“BDS.txt”共筛选出6578个与BDS相关的DEGs（图1D）。", "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:38645867"], "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:GSE192867"], "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:GSE192867"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38645867", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.12182/20240360402", "sha256": "sha256:5dd83f5f47af2febed7fe04dbe48cfe3f69894ce98a041358d33f8ce8414bc34", "bytes": 18392, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.12182/20240360402", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11026890", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE192867", "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=GSE192867", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE192867", "version": null, "note": "通过GEO数据库（http://www.ncbi. nlm.nih.gov/geo/）下载GSE192867数据集。该数据集中有10例来自健康人群，有62例PV患者（其中BHS患者16例、BSS患者23例、BDS患者23例）。在数据集中，用Affymetrix Human Clariom D Assay检测健康人群和PV患者外周血单核细胞转录组的表达。", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "通过GEO数据库（http://www.ncbi. nlm.nih.gov/geo/）下载GSE192867数据集。该数据集中有10例来自健康人群，有62例PV患者（其中BHS患者16例、BSS患者23例、BDS患者23例）。在数据集中，用Affymetrix Human Clariom D Assay检测健康人群和PV患者外周血单核细胞转录组的表达。", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM5767684", "GSM5767685", "GSM5767686", "GSM5767687", "GSM5767688", "GSM5767689", "GSM5767690", "GSM5767691", "GSM5767692", "GSM5767693", "GSM5767694", "GSM5767695", "GSM5767696", "GSM5767697", "GSM5767698", "GSM5767699", "GSM5767700", "GSM5767701", "GSM5767702", "GSM5767703", "GSM5767704", "GSM5767705", "GSM5767706", "GSM5767707", "GSM5767708", "GSM5767709", "GSM5767710", "GSM5767711", "GSM5767712", "GSM5767713", "GSM5767714", "GSM5767715", "GSM5767716", "GSM5767717", "GSM5767718", "GSM5767719", "GSM5767720", "GSM5767721", "GSM5767722", "GSM5767723", "GSM5767724", "GSM5767725", "GSM5767726", "GSM5767727", "GSM5767728", "GSM5767729", "GSM5767730", "GSM5767731", "GSM5767732", "GSM5767733", "GSM5767734", "GSM5767735", "GSM5767736", "GSM5767737", "GSM5767738", "GSM5767739", "GSM5767740", "GSM5767741", "GSM5767742", "GSM5767743", "GSM5767744", "GSM5767745", "GSM5767746", "GSM5767747", "GSM5767748", "GSM5767749", "GSM5767750", "GSM5767751", "GSM5767752", "GSM5767753", "GSM5767754", "GSM5767755"], "sample_count": 72, "group_sizes": null, "group_sizes_basis": null, "platform": "23126", "taxon": "Homo sapiens", "title": "The Gene Expression Analysis of Peripheral Blood Monocytes from Psoriasis Vulgaris Patients with Different Traditional Chinese Medicine (TCM) Syndromes", "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:GSE192867 not downloaded", "asset:data:geo:GSE192867 licence not read"]}, "analysis": {"state": "partial", "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": 0.7, "band": "medium", "quote": "limma"}}, {"id": "method-2", "family": "machine_learning", "specific": "random_forest", "label": "Machine learning", "dsl_operations": [], "missing_operations": ["machine_learning_random_forest"], "expressible": false, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "random forest"}}, {"id": "method-3", "family": "machine_learning", "specific": "support_vector_machine", "label": "Machine learning", "dsl_operations": ["train_classifier", "cross_validate", "roc_auc"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "support vector machine"}}, {"id": "method-4", "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"}}, {"id": "method-5", "family": null, "specific": null, "label": "利用limma包进行差异分析，并以|log2(fold change, FC)|>3，P<0.05为标准筛选差异表达基因", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "利用limma包分别对“PV.txt”、“BHS.txt”、“BSS.txt”和“BDS.txt”文件进行差异分析[10]。以|log2(fold change, FC)|>3，P<0.05为标准筛选差异表达基因（differentially expressed genes, DEGs），并绘制火山图。"}}], "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": ["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": ["GSE192867"], "resolved_accessions": ["GSE192867"], "statements": ["通过GEO数据库（http://www.ncbi. nlm.nih.gov/geo/）下载GSE192867数据集。该数据集中有10例来自健康人群，有62例PV患者（其中BHS患者16例、BSS患者23例、BDS患者23例）。在数据集中，用Affymetrix Human Clariom D Assay检测健康人群和PV患者外周血单核细胞转录组的表达。"], "basis": "The paper names GSE192867 in 基因表达数据库（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:38645867", "data:geo:GSE192867"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE192867"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:16:30Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 5, "usage": {"prompt_tokens": 9466, "completion_tokens": 1328, "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:38645867", "type": "paper", "label": "pmid:38645867"}, {"id": "source:pmid:38645867", "type": "manuscript", "label": "PMID 38645867 full text"}, {"id": "data:geo:GSE192867", "type": "dataset", "label": "GEO GSE192867"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:38645867", "type": "paper", "label": "pmid:38645867"}, {"id": "source:pmid:38645867", "type": "manuscript", "label": "PMID 38645867 full text"}, {"id": "data:geo:GSE192867", "type": "dataset", "label": "GEO GSE192867"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-38645867", "type": "extraction", "used": ["source:pmid:38645867"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE192867", "type": "accession_resolution", "used": ["data:geo:GSE192867"], "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:38645867", "parent_hash": "sha256:aa7e47679c04f0b23da0e697e735e7186696379d208d3b2514bb26bb259b0595", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE192867 licence not read", "asset:data:geo:GSE192867 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": 0.69, "evidence": ["P), mitogen-activated protein kinase (MAPK), apoptosis, and other pathways. A total of 13 key chara"], "order_basis": "paper_text_order:1798", "id": "assay:1"}, {"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.69, "evidence": ["key characteristic genes of BSS; recombinant mouse protein (RRNAD1), GTPase-activating protein"], "order_basis": "paper_text_order:2451", "id": "assay:2"}, {"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": 0.7, "evidence": ["limma"], "order_basis": "consumes_earlier_output", "id": "assay:3"}]},"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":"2026-11-04T03:12:33+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}}}