{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38898266", "kind": "science-record", "revision": 4, "content_hash": "sha256:f3163488191ec090433a1400da88b5ef88c7e429e6dbea6785a0b8fadd45181f", "created_at": "2026-11-01T20:28:58Z", "updated_at": "2026-11-01T22:54:32Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "RARRES1 identified by comprehensive bioinformatic analysis and experimental validation as a promising biomarker in Skin Cutaneous Melanoma.", "doi": "10.1038/s41598-024-65032-1", "pmid": "38898266", "authors": ["Meng Liu", "Ruimin Bai", "Guanfei Zhang", "Xinyi Liu", "Ziyang Wang", "Ke He", "Xinyi Gan", "Xiaolin Zhou", "Pan Yin", "Yan Zheng", "Guorong Wang"], "journal": "Scientific reports", "year": 2024, "abstract": "Skin cutaneous melanoma (SKCM) is a highly malignant form of skin cancer, known for its unfavorable prognosis and elevated mortality rate. RARRES1, a gene responsive to retinoic acid receptors, displays varied functions in various cancer types. However, the specific role and underlying mechanisms of RARRES1 in SKCM are still unclear. GSE15605 was utilized to analyze the expression of RARRES1 in SKCM. Subsequently, the TCGA and GEO databases were employed to investigate the relationships between RARRES1 and clinicopathological parameters, as well as the prognostic implications and diagnostic efficacy of RARRES1 in SKCM. GO, KEGG, and GSEA analyses were conducted to explore the potential functions of RARRES1. Furthermore, the associations between RARRES1 and immune infiltration were examined. Genomic alterations and promoter methylation levels of RARRES1 in SKCM were assessed using cBioPortal, UALCAN, and the GEO database. Finally, RARRES1 expression in SKCM was validated through immunohistochemistry, and its functional role in SKCM progression was elucidated via in vivo and in vitro experiments. We found that RARRES1 was downregulated in SKCM compared with normal tissues, and this low expression was associated with worse clinicopathological features and poor prognosis of SKCM. The diagnostic efficacy of RARRES1, as determined by ROC analysis, was 0.732. Through GO, KEGG, and GSEA enrichment analysis, we identified 30 correlated genes and pathways that were mainly enriched in the tumor immune microenvironment, proliferation, apoptosis, and autophagy. Additionally, RARRES1 expression was found to be positively related to the infiltration of various immune cells in SKCM, particularly macrophages and T helper cells, among others. Analysis of genomic alterations and promoter methylation revealed that shallow deletion and hypermethylation of the RARRES1 promoter could lead to reduced RARRES1 expression. IHC validation confirmed the downregulation of RARRES1 in SKCM. Moreover, overexpression of RARRES1 inhibited the proliferation and migration of A375 cells, promoted apoptosis, and inhibited autophagic flux. In the mouse xenograft model, RARRES1 overexpression also suppressed SKCM tumor growth. Collectively, these findings suggest that RARRES1 may function as a suppressor and could potentially serve as a prognostic biomarker and therapeutic target for SKCM.", "claims": [{"id": "claim-method", "statement": "Kaplan–Meier survival curves were constructed to compare the prognosis between the high and low RARRES1 groups. Additionally, univariate and multivariate Cox regression analyses were employed to assess the risk factors associated with SKCM. For the ROC analysis, the expression data of RARRES1 in the GSE15605 dataset was processed by Graphpad prism.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38898266", "locator": "sections[4] \"Prognostic analysis\" paragraph 2", "quote": "Kaplan–Meier survival curves were constructed to compare the prognosis between the high and low RARRES1 groups."}, {"asset": "source:pmid:38898266", "locator": "sections[4] \"Prognostic analysis\" paragraph 2", "quote": "Additionally, univariate and multivariate Cox regression analyses were employed to assess the risk factors associated with SKCM."}, {"asset": "source:pmid:38898266", "locator": "sections[4] \"Prognostic analysis\" paragraph 2", "quote": "For the ROC analysis, the expression data of RARRES1 in the GSE15605 dataset was processed by Graphpad prism."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets featured in this study are available in online repositories, and the names of these repositories along with their respective accession numbers can be located within the article. The GSE15605 and GSE120878 datasets were downloaded from the GEO (https://www.ncbi.nlm.nih.gov/geo/) database. Patient information and prognosis data of SKCM was obtained from TCGA (https://www.cancer.gov/ccg/research/genome-sequencing/tcga).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38898266", "locator": "sections[41] \"Data availability\" paragraph 2", "quote": "The datasets featured in this study are available in online repositories, and the names of these repositories along with their respective accession numbers can be located within the article. The GSE15605 and GSE120878 datasets were downloaded from the GEO (https://www.ncbi.nlm.nih.gov/geo/) database. Patient information and prognosis data of SKCM was obtained from TCGA (https://www.cancer.gov/ccg/research/genome-sequencing/tcga)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "RARRES1 showed diagnostic performance for SKCM, with a ROC AUC of 0.732 (P = 0.0048), while low expression was associated with adverse clinical features and poor prognosis.", "kind": "quantitative", "target": {"value": 0.0048, "unit": "p-value", "tolerance": null, "source": "Based on the expression data of RARRES1 in GSE15605, the diagnostic value of RARRES1 in SKCM was calculated, the area under the curve (AUC) was 0.732 (P = 0.0048), which illustrated that RARRES1 had a good diagnostic performance in SKCM21 (Fig. 1N)."}, "evidence": [{"asset": "source:pmid:38898266", "locator": "sections[27] \"Expression, clinicopathological correlation, prognostic and diagnostic potential of RARRES1 in SKCM\" paragraph 2", "quote": "Based on the expression data of RARRES1 in GSE15605, the diagnostic value of RARRES1 in SKCM was calculated, the area under the curve (AUC) was 0.732 (P = 0.0048), which illustrated that RARRES1 had a good diagnostic performance in SKCM21 (Fig. 1N)."}, {"asset": "source:pmid:38898266", "locator": "sections[27] \"Expression, clinicopathological correlation, prognostic and diagnostic potential of RARRES1 in SKCM\" paragraph 2", "quote": "The Kaplan–Meier survival analysis indicated that low expression of RARRES1 was associated with unfavorable overall survival (OS) or disease specific survival (DSS) (Fig. 1I–J)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "RARRES1 showed diagnostic performance for SKCM, with a ROC AUC of 0.732 (P = 0.0048), while low expression was associated with adverse clinical features and poor prognosis.", "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:38898266"], "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:GSE120878"], "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:GSE120878"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38898266", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1038/s41598-024-65032-1", "sha256": "sha256:88b626db84a0b0faf8380e850377804fb2a81410dc0a59859bf088251568b444", "bytes": 55380, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1038/s41598-024-65032-1", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11187141", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE120878", "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=GSE120878", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE120878", "version": null, "note": "The datasets featured in this study are available in online repositories, and the names of these repositories along with their respective accession numbers can be located within the article. The GSE15605 and GSE120878 datasets were downloaded from the GEO (https://www.ncbi.nlm.nih.gov/geo/) database. Patient information and prognosis data of SKCM was obtained from TCGA (https://www.cancer.gov/ccg/research/genome-sequencing/tcga).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets featured in this study are available in online repositories, and the names of these repositories along with their respective accession numbers can be located within the article. The GSE15605 and GSE120878 datasets were downloaded from the GEO (https://www.ncbi.nlm.nih.gov/geo/) database. 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The GSE15605 and GSE120878 datasets were downloaded from the GEO (https://www.ncbi.nlm.nih.gov/geo/) database. Patient information and prognosis data of SKCM was obtained from TCGA (https://www.cancer.gov/ccg/research/genome-sequencing/tcga).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets featured in this study are available in online repositories, and the names of these repositories along with their respective accession numbers can be located within the article. The GSE15605 and GSE120878 datasets were downloaded from the GEO (https://www.ncbi.nlm.nih.gov/geo/) database. Patient information and prognosis data of SKCM was obtained from TCGA (https://www.cancer.gov/ccg/research/genome-sequencing/tcga).", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM390208", "GSM390209", "GSM390210", "GSM390211", "GSM390212", "GSM390213", "GSM390214", "GSM390215", "GSM390216", "GSM390217", "GSM390218", "GSM390219", "GSM390220", "GSM390221", "GSM390222", "GSM390223", "GSM390224", "GSM390225", "GSM390226", "GSM390227", "GSM390228", "GSM390229", "GSM390230", "GSM390231", "GSM390232", "GSM390233", "GSM390234", "GSM390235", "GSM390236", "GSM390237", "GSM390238", "GSM390239", "GSM390240", "GSM390241", "GSM390242", "GSM390243", "GSM390244", "GSM390245", "GSM390246", "GSM390247", "GSM390248", "GSM390249", "GSM390250", "GSM390251", "GSM390252", "GSM390253", "GSM390254", "GSM390255", "GSM390256", "GSM390257", "GSM390258", "GSM390259", "GSM390260", "GSM390261", "GSM390262", "GSM390263", "GSM390264", "GSM390265", "GSM390266", "GSM390267", "GSM390268", "GSM390269", "GSM390270", "GSM390271", "GSM390272", "GSM390273", "GSM390274", "GSM390275", "GSM390276", "GSM390277", "GSM390278", "GSM390279", "GSM390280", "GSM390281"], "sample_count": 74, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Transcriptome profiling identifies HMGA2 as a novel gene in melanoma progression", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE120878 not downloaded", "asset:data:geo:GSE120878 licence not read", "asset:data:geo:GSE15605 not downloaded", "asset:data:geo:GSE15605 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "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": 1.0, "band": "reordered", "quote": "Kaplan–Meier survival curves were constructed to compare the prognosis between the high and low RARRES1 groups. Additionally, univariate and multivariate Cox regression analyses were employed to assess the risk factors associated with SKCM. For the ROC analysis, the expression data of RARRES1 in the GSE15605 dataset was processed by Graphpad prism."}}, {"id": "method-2", "family": "group_comparison", "specific": "student_t_test", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["student_t"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Student's t-test"}}, {"id": "method-3", "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-4", "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-5", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "Logrank"}}, {"id": "method-6", "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": 0.8, "band": "high", "quote": "pathway enrichment"}}, {"id": "method-7", "family": "diagnostic_evaluation", "specific": "roc", "label": "Diagnostic test evaluation", "dsl_operations": ["confusion_counts", "roc_curve", "sensitivity_specificity", "solve_confusion_matrix", "classification_metrics", "published_precision_envelope"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["reference_standard_and_test"], "evidence": {"score": 0.7, "band": "medium", "quote": "ROC analysis"}}], "targets": [{"id": "target-published-estimate", "claim_id": "claim-target-result", "operation": "classification_metrics", "expected_value": 0.0048, "unit": "p-value", "tolerance": null, "state": "complete", "note": "The threshold the paper applied to its own result, as the paper states it. A run that reproduces the effect is judged against this threshold."}], "gaps": ["method.reader_differs_from_extractor"]}, "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": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "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": ["GSE15605", "GSE120878"], "resolved_accessions": ["GSE15605", "GSE120878"], "statements": ["The datasets featured in this study are available in online repositories, and the names of these repositories along with their respective accession numbers can be located within the article. The GSE15605 and GSE120878 datasets were downloaded from the GEO (https://www.ncbi.nlm.nih.gov/geo/) database. Patient information and prognosis data of SKCM was obtained from TCGA (https://www.cancer.gov/ccg/research/genome-sequencing/tcga)."], "basis": "The paper names GSE15605, GSE120878 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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IHC validation confirmed the downregulation of R"], "order_basis": "paper_text_order:1088", "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": 0.99, "evidence": ["role in SKCM progression was elucidated via in vivo and in vitro experiments. We found that RARR", "ed apoptosis, and inhibited autophagic flux. In the mouse xenograft model, RARRES1 overexpression also", "tosis, and inhibited autophagic flux. In the mouse xenograft model, RARRES1 overexpression also"], "order_basis": "paper_text_order:1174", "id": "assay:2"}, {"role": "data_generation", "definition_id": "apoptosis_assay", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["umor immune microenvironment, proliferation, apoptosis, and autophagy. Additionally, RARRES1 expres", "ration and migration of A375 cells, promoted apoptosis, and inhibited autophagic flux. In the mouse", "otic G1 Phase and G1/S transition (Fig. 2D), caspase cascade (Fig. 2E), oxidative damage response", "D) mitotic G1 phase and G1/S transition, (E) caspase cascade, (F) oxidative damage response, (G)"], "order_basis": "paper_text_order:1644", "id": "assay:3"}, {"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["a of RARRES1 in SKCM and normal samples. The RNAseq data for SKCM was acquired from the TCGA dat"], "order_basis": "paper_text_order:2808", "id": "assay:4"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.77, "evidence": ["The A375 cells were purchased from ATCC and cultured in Dulbecco’s modified Eagle’s medium containin"], "order_basis": "paper_text_order:4749", "id": "assay:5"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Kaplan–Meier survival curves were constructed to compare the prognosis between the high and low RARRES1 groups. Additionally, univariate and multivariate Cox regression analyses were employed to assess the risk factors associated with SKCM. For the ROC analysis, the expression data of RARRES1 in the GSE15605 dataset was processed by Graphpad prism."], "order_basis": "consumes_earlier_output", "id": "assay:6"}]},"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":"2026-11-04T02:16:50+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}}}