{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:30704460", "kind": "science-record", "revision": 6, "content_hash": "sha256:836cb1ef76b2868f92f80374eb308993d7509b90f0977a188f459c511722cb74", "created_at": "2026-11-01T15:40:41Z", "updated_at": "2026-11-01T21:21:57Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integration of genomic copy number variations and chemotherapy-response biomarkers in pediatric sarcoma.", "doi": "10.1186/s12920-018-0456-5", "pmid": "30704460", "authors": ["Lijun Cheng", "Pankita H Pandya", "Enze Liu", "Pooja Chandra", "Limei Wang", "Mary E Murray", "Jacquelyn Carter", "Michael Ferguson", "Mohammad Reza Saadatzadeh", "Khadijeh Bijangi-Visheshsaraei", "Mark Marshall", "Lang Li", "Karen E Pollok", "Jamie L Renbarger"], "journal": "BMC medical genomics", "year": 2019, "abstract": "BACKGROUND: While most pediatric sarcomas respond to front-line therapy, some bone sarcomas do not show radiographic response like soft-tissue sarcomas (rhabdomyosarccomas) but do show 90% necrosis. Though, new therapies are urgently needed to improve survival and quality of life in pediatric patients with sarcomas. Complex chromosomal aberrations such as amplifications and deletions of DNA sequences are frequently observed in pediatric sarcomas. Evaluation of copy number variations (CNVs) associated with pediatric sarcoma patients at the time of diagnosis or following therapy offers an opportunity to assess dysregulated molecular targets and signaling pathways that may drive sarcoma development, progression, or relapse. The objective of this study was to utilize publicly available data sets to identify potential predictive biomarkers of chemotherapeutic response in pediatric Osteosarcoma (OS), Rhabdomyosarcoma (RMS) and Ewing's Sarcoma Family of Tumors (ESFTs) based on CNVs following chemotherapy (OS n = 117, RMS n = 64, ESFTs n = 25 tumor biopsies).\nMETHODS: There were 206 CNV profiles derived from pediatric sarcoma biopsies collected from the public databases TARGET and NCBI-Gene Expression Omnibus (GEO). Through our comparative genomic analyses of OS, RMS, and ESFTs and 22,255 healthy individuals called from the Database of Genomic Variants (DGV), we identified CNVs (amplifications and deletions) pattern of genomic instability in these pediatric sarcomas. By integrating CNVs of Cancer Cell Line Encyclopedia (CCLE) identified in the pool of genes with drug-response data from sarcoma cell lines (n = 27) from Cancer Therapeutics Response Portal (CTRP) Version 2, potential predictive biomarkers of therapeutic response were identified.\nRESULTS: Genes associated with survival and/recurrence of these sarcomas with statistical significance were found on long arm of chromosome 8 and smaller aberrations were also identified at chromosomes 1q, 12q and x in OS, RMS, and ESFTs. A pool of 63 genes that harbored amplifications and/or deletions were frequently associated with recurrence across OS, RMS, and ESFTs. Correlation analysis of CNVs from CCLE with drug-response data of CTRP in 27 sarcoma cell lines, 33 CNVs out of 63 genes correlated with either sensitivity or resistance to 17 chemotherapies from which actionable CNV signatures such as IGF1R, MYC, MAPK1, ATF1, and MDM2 were identified. These CNV signatures could potentially be used to delineate patient populations that will respond versus those that will not respond to a particular chemotherapy.\nCONCLUSIONS: The large-scale analyses of CNV-drug screening provides a platform to evaluate genetic alterations across aggressive pediatric sarcomas. Additionally, this study provides novel insights into the potential utilization of CNVs as not only prognostic but also as predictive biomarkers of therapeutic response. Information obtained in this study may help guide and prioritize patient-specific therapeutic options in pediatric bone and soft-tissue sarcomas.", "claims": [{"id": "claim-method", "statement": "Pearson correlation coefficient is used to calculate association between drug response AUC and copy number variation in each of gene.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30704460", "locator": "sections[21] \"Statistical analysis\" paragraph 2", "quote": "Pearson correlation coefficient is used to calculate association between drug response AUC and copy number variation in each of gene."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analyzed during the current study are available in the DGV database [20], http://dgv.tcag.ca/dgv/app/home; CCLE [21], https://portals.broadinstitute.org/ccle; CTRP [22] https://portals.broadinstitute.org/ctrp.v2.1/; GEO repository [https://www.ncbi.nlm.nih.gov/sites/GDSbrowser/], https://www.ncbi.nlm.nih.gov/geo/ and TARGET Data Matrix [https://ocg.cancer.gov/programs/target], https://ocg.cancer.gov/programs/target/data-matrix.\n\nAll data annotation and results during this study are included in this published article and its supplementary information files, Additional files 1, 2, 3 and 4.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30704460", "locator": "sections[26] \"Availability of data and materials\" paragraphs 1-3", "quote": "The datasets analyzed during the current study are available in the DGV database [20], http://dgv.tcag.ca/dgv/app/home; CCLE [21], https://portals.broadinstitute.org/ccle; CTRP [22] https://portals.broadinstitute.org/ctrp.v2.1/; GEO repository [https://www.ncbi.nlm.nih.gov/sites/GDSbrowser/], https://www.ncbi.nlm.nih.gov/geo/ and TARGET Data Matrix [https://ocg.cancer.gov/programs/target], https://ocg.cancer.gov/programs/target/data-matrix.\n\nAll data annotation and results during this study are included in this published article and its supplementary information files, Additional files 1, 2, 3 and 4."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": null, "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:30704460"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:30704460", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12920-018-0456-5", "sha256": "sha256:c781fad806699981721414adfa63b9ff73e18932bd7fc0f2a9dc3e972647f139", "bytes": 60539, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12920-018-0456-5", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC6357363", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "asset:table:pmid:30704460:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:4569e0f8abbea2b19ab2545c43f26f13b17de7a24b55431263222f725302e007", "bytes": 795, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[2]/table-wrap[1]#Tab1", "version": null, "note": "Datasets and their source for healthy and pediatric sarcoma patients", "structure": {"pmcid": "PMC6357363", "section_index": 2, "section_title": "Samples and clinical data", "row_count": 6, "column_count": 4}, "table": {"label": "Table 1", "caption": "Datasets and their source for healthy and pediatric sarcoma patients", "rows": [["Data Type", "Source", "Platform", "Sample size"], ["Healthy Individuals", "DGV (Database of Genomic Variants) [13]", "BAC Acgh, FISH, OligoACGH, PCR, Sequencing, SNP array and Digital array", "22, 255"], ["Osteosarcoma (OS)", "GEO (GSE33383)TARGET", "Affymetrix Genome-Wide Human SNP6.0 Array chips, GPL6801", "3285"], ["Rhabdomyosarcoma (RMS)", "GEO (GSE24715)", "Affymetrix Mapping 250 K Sty2 SNP chips, GPL3720", "7"], ["Affymetrix Human Mapping 50 K Xba240 SNP chips, GPL2005", "57"], ["Ewing Sarcoma (ESFTs)", "GEO (GSE8398)", "Agilent-013282 Human Genome CGH Microarray 44B, GPL2879", "25"]], "row_count": 6, "column_count": 4, "numeric_cells": 13, "header_rows": 1, "locator": "section[2]/table-wrap[1]#Tab1"}}, {"id": "asset:table:pmid:30704460:2", 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"Ewings_sarcoma", "TC-71"], ["soft_tissue", "Rhabdomyosarcoma", "RH-30", "bone", "Osteosarcoma", "143B"], ["soft_tissue", "Rhabdomyosarcoma", "RH-41", "bone", "Osteosarcoma", "G-292"], ["soft_tissue", "Rhabdomyosarcoma", "SJRH30", "bone", "Osteosarcoma", "HOS"], ["soft_tissue", "Rhabdomyosarcoma", "TE 441.T", "bone", "Osteosarcoma", "Hs 870.T"], ["soft_tissue", "Rhabdomyosarcoma", "TE 617.T", "bone", "Osteosarcoma", "Hs 888.T"], ["bone", "Ewings_sarcoma", "A-673", "bone", "Osteosarcoma", "MG-63"], ["bone", "Ewings_sarcoma", "CADO-ES1", "bone", "Osteosarcoma", "SJSA-1"], ["bone", "Ewings_sarcoma", "Hs 822.T", "bone", "Osteosarcoma", "T1–73"], ["bone", "Ewings_sarcoma", "Hs 863.T", "bone", "Osteosarcoma", "U-2 OS"], ["bone", "Ewings_sarcoma", "MHH-ES-1", "", "", ""]], "row_count": 15, "column_count": 6, "numeric_cells": 22, "header_rows": 1, "locator": "section[2]/table-wrap[2]#Tab2"}}, {"id": "asset:table:pmid:30704460:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:d42c087616b19ee64a4ce253decab60374dd620fa8afb62a7c36b68116a4417d", "bytes": 5659, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[5]/table-wrap[1]#Tab3", "version": null, "note": "CNVs (amplifications and/or deletions) frequently found in the 63 genes that serve as prognostic biomarkers for pediatric sarcomas (OS, RMS, and ESFTS)", "structure": {"pmcid": "PMC6357363", "section_index": 5, "section_title": "Significant CNVs associated with prognostic biomarkers of pediatric sarcomas (OS, RMS, ESFTs)", "row_count": 65, "column_count": 12}, "table": {"label": "Table 3", "caption": "CNVs (amplifications and/or deletions) frequently found in the 63 genes that serve as prognostic biomarkers for pediatric sarcomas (OS, RMS, and ESFTS)", "rows": [["", "OS frequency", "RMS frequency", "ESFT frequency", "Sarcoma types (Yes = 1)"], ["NO", "Band", "Gene", "Amp", "Del", "Amp", "Del", "Amp", "Del", "OS", "RMS", "ESFT"], ["1", "7p11.2", "EGFRa", "0.250", "0.094", "0.087", "0.109", "0.438", "0.000", "1", "1", "1"], ["2", "12q13.3", "GLI1", "0.156", "0.375", "0.891", "0.000", "0.313", "0.188", "", "1", "1"], ["3", "2q36.1", "PAX3", "0.063", "0.531", "0.413", "0.000", "0.250", "0.063", "", "1", "1"], ["4", "7q36.1", "EZH2a", "0.344", "0.094", "0.413", "0.000", "0.313", "0.125", "", "1", "1"], ["5", "8q24.21", "MYC", "0.781", "0.031", "0.043", "0.326", "0.625", "0.000", "1", "1", ""], ["6", "8q24.22", "LRRC6", "0.625", "0.031", "0.391", "0.043", "0.625", "0.063", "1", "1", ""], ["7", "8q24.13", "MTSS1", "0.625", "0.063", "0.283", "0.000", "0.438", "0.000", "1", "1", ""], ["8", "15q11.2", "MKRN3", "0.219", "0.188", "0.065", "0.109", "0.438", "0.125", "1", "1", ""], ["9", "11q24.2", "ST3GAL4", "0.156", "0.281", "0.174", "0.130", "0.438", "0.125", "1", "1", ""], ["10", "15q22.2", "TPM1", "0.094", "0.156", "0.000", "0.261", "0.125", "0.063", "1", "1", 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["Stage2", "Metastatic", "22"], ["Non-Metastatic", "63"], ["Gender", "Female", "37"], ["Male", "48"], ["Vital Status", "Alive", "55"], ["Dead", "30"], ["Age", "At the time of Diagnosis (days):1299–11,828", "85"], ["High Grade OS", "GEO-GSE33383", "Age", "At the time of Diagnosis (days):3072–14,965", "32"], ["ESFTs", "GEO-GSE8398", "Gender", "Female", "11"], ["Male", "9"], ["Unknown", "5"], ["Stage", "Metastatic", "11"], ["Localized", "9"], ["Unknown", "5"], ["RMS", "GEO-GSE24715", "Histology Subtype", "ARMS (Alveolar rhabdomyosarcoma)", "64"]], "row_count": 18, "column_count": 5, "numeric_cells": 22, "header_rows": 1, "locator": "section[13]/table-wrap[1]#Tab4"}}], "gaps": []}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "correlation_analysis", "specific": "pearson", "label": "Correlation analysis", "dsl_operations": ["pearson_r"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Pearson correlation coefficient is used to calculate association between drug response AUC and copy number variation in each of gene."}}, {"id": "method-2", "family": "clustering", "specific": "hierarchical", "label": "Clustering", "dsl_operations": ["hierarchical_cluster"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["feature_matrix"], "evidence": {"score": 0.8, "band": "high", "quote": "hierarchical clustering"}}], "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": "blocked", "tier": "R4", "blocking_axis": "data", "blocked_on": "data:accession_absent", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["pearson_r"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: pearson."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R4", "reachable": false, "accessions": [], "resolved_accessions": [], "statements": ["The datasets analyzed during the current study are available in the DGV database [20], http://dgv.tcag.ca/dgv/app/home; CCLE [21], https://portals.broadinstitute.org/ccle; CTRP [22] https://portals.broadinstitute.org/ctrp.v2.1/; GEO repository [https://www.ncbi.nlm.nih.gov/sites/GDSbrowser/], https://www.ncbi.nlm.nih.gov/geo/ and TARGET Data Matrix [https://ocg.cancer.gov/programs/target], https://ocg.cancer.gov/programs/target/data-matrix.\n\nAll data annotation and results during this study are included in this published article and its supplementary information files, Additional files 1, 2, 3 and 4."], "basis": "The paper names no accession to its source data, so the data has to come from the authors."}}, "can_run": {"dsl_operations": ["pearson_r"], "assets": ["source:pmid:30704460", "asset:table:pmid:30704460:1", "asset:table:pmid:30704460:2", "asset:table:pmid:30704460:3", "asset:table:pmid:30704460:4"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:None"]}, "gaps": ["data:accession_absent"]}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:13:38Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 3, "usage": {"prompt_tokens": 47544, "completion_tokens": 2170, "cached_tokens": 15880}}, "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:30704460", "type": "paper", "label": "pmid:30704460"}, {"id": "source:pmid:30704460", "type": "manuscript", "label": "PMID 30704460 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:30704460", "type": "paper", "label": "pmid:30704460"}, {"id": "source:pmid:30704460", "type": "manuscript", "label": "PMID 30704460 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-30704460", "type": "extraction", "used": ["source:pmid:30704460"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-None", "type": "accession_resolution", "used": ["data:geo:None"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:30704460", "parent_hash": "sha256:ba899234f6a9346911d6c7cd454a8cc704d9605fa46133a6410287d5f3b9c9db", "fork_of": null, "generation": 5}, "gaps": ["execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique", "step:obtain_source_data blocked on data:accession_absent"], "assays": [{"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ma cancer cells lines previously obtained by Affymetrix SNP Array 6.0 were collected (see Table 2 fo", "ent of CNVs using high-resolution array CGH (Affymetrix SNP) array was completed on OS, RMS and ESFT"], "order_basis": "paper_text_order:4321", "id": "assay:1"}, {"role": "analysis", "definition_id": "correlation_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["pearson_r"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Pearson correlation coefficient is used to calculate association between drug response AUC and copy number variation in each of gene."], "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":"2026-11-04T01:43:00+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}}}