{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:26217797", "kind": "science-record", "revision": 6, "content_hash": "sha256:974c82fedcf3d6e29b77a43747b1124150bb5453448880b9aa7dc295284a87e1", "created_at": "2026-11-01T15:40:09Z", "updated_at": "2026-11-01T21:20:03Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Prenatal alcohol exposure alters gene expression in the rat brain: Experimental design and bioinformatic analysis of microarray data.", "doi": "10.1016/j.dib.2015.05.007", "pmid": "26217797", "authors": ["Alexandre A Lussier", "Katarzyna A Stepien", "Joanne Weinberg", "Michael S Kobor"], "journal": "Data in brief", "year": 2015, "abstract": "We previously identified gene expression changes in the prefrontal cortex and hippocampus of rats prenatally exposed to alcohol under both steady-state and challenge conditions (Lussier et al., 2015, Alcohol.: Clin. Exp. Res., 39, 251-261). In this study, adult female rats from three prenatal treatment groups (ad libitum-fed control, pair-fed, and ethanol-fed) were injected with physiological saline solution or complete Freund׳s adjuvant (CFA) to induce arthritis (adjuvant-induced arthritis, AA). The prefrontal cortex and hippocampus were collected 16 days (peak of arthritis) or 39 days (during recovery) following injection, and whole genome gene expression was assayed using Illumina׳s RatRef-12 expression microarray. Here, we provide additional metadata, detailed explanations of data pre-processing steps and quality control, as well as a basic framework for the bioinformatic analyses performed. The datasets from this study are publicly available on the GEO repository (accession number GSE63561).", "claims": [{"id": "claim-method", "statement": "In order to correct for these unknown variables, as well as significant batch effects in the two datasets, surrogate variable analysis (sva) was used to generate variables representative of expression heterogeneity within the two datasets [7].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:26217797", "locator": "sections[14] \"Differential expression analysis\" paragraph 2", "quote": "In order to correct for these unknown variables, as well as significant batch effects in the two datasets, surrogate variable analysis (sva) was used to generate variables representative of expression heterogeneity within the two datasets [7]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Probe-level data for this study were deposited on the GEO (GSE63561), along with metadata describing experimental treatment groups. As described, spatial artifacts were masked from the dataset and data were log 2-transformed prior to submission of raw and quantile-normalized data. Moreover, due to GEO submission requirements, the datasets were filtered to include only probes associated with a gene. As such, the current GEO files do not contain any control probes, although these additional data are available upon request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:26217797", "locator": "sections[16] \"GEO submission\" paragraph 2", "quote": "Probe-level data for this study were deposited on the GEO (GSE63561), along with metadata describing experimental treatment groups. As described, spatial artifacts were masked from the dataset and data were log 2-transformed prior to submission of raw and quantile-normalized data. Moreover, due to GEO submission requirements, the datasets were filtered to include only probes associated with a gene. As such, the current GEO files do not contain any control probes, although these additional data are available upon request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study used surrogate variable analysis to generate covariates for limma linear modeling, controlled the false-discovery rate at 25% with Benjamini–Hochberg correction, and deposited raw and quantile-normalized probe-level data in GEO under accession GSE63561.", "kind": "quantitative", "target": {"value": 25.0, "unit": "per cent", "tolerance": null, "source": "As the effects of experimental treatments were subtle, the false-discovery rate (FDR) was controlled at 25% (q-value <0.25)."}, "evidence": [{"asset": "source:pmid:26217797", "locator": "sections[14] \"Differential expression analysis\" paragraph 2", "quote": "This method identifies eigenvectors of variation not associated with primary variables, which can then be incorporated as covariates during linear modeling to remove unwanted sources of heterogeneity."}, {"asset": "source:pmid:26217797", "locator": "sections[14] \"Differential expression analysis\" paragraph 4", "quote": "Surrogate variables generated by sva were included as covariates in linear modeling of gene expression using the limma package in the statistical program R [11]."}, {"asset": "source:pmid:26217797", "locator": "sections[14] \"Differential expression analysis\" paragraph 4", "quote": "As the effects of experimental treatments were subtle, the false-discovery rate (FDR) was controlled at 25% (q-value <0.25)."}, {"asset": "source:pmid:26217797", "locator": "sections[16] \"GEO submission\" paragraph 2", "quote": "Probe-level data for this study were deposited on the GEO (GSE63561), along with metadata describing experimental treatment groups."}, {"asset": "source:pmid:26217797", "locator": "sections[16] \"GEO submission\" paragraph 2", "quote": "As described, spatial artifacts were masked from the dataset and data were log 2-transformed prior to submission of raw and quantile-normalized data."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study used surrogate variable analysis to generate covariates for limma linear modeling, controlled the false-discovery rate at 25% with Benjamini–Hochberg correction, and deposited raw and quantile-normalized probe-level data in GEO under accession GSE63561.", "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:26217797"], "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:GSE63561"], "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:GSE63561"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:26217797", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1016/j.dib.2015.05.007", "sha256": "sha256:b5494af43e4ffe4888099fe00be0983a8b737688ac2e4b6bcd0282e14db09165", "bytes": 34344, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1016/j.dib.2015.05.007", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC4510447", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE63561", "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=GSE63561", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE63561", "version": null, "note": "Probe-level data for this study were deposited on the GEO (GSE63561), along with metadata describing experimental treatment groups. As described, spatial artifacts were masked from the dataset and data were log 2-transformed prior to submission of raw and quantile-normalized data. Moreover, due to GEO submission requirements, the datasets were filtered to include only probes associated with a gene. As such, the current GEO files do not contain any control probes, although these additional data are available upon request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Probe-level data for this study were deposited on the GEO (GSE63561), along with metadata describing experimental treatment groups. As described, spatial artifacts were masked from the dataset and data were log 2-transformed prior to submission of raw and quantile-normalized data. Moreover, due to GEO submission requirements, the datasets were filtered to include only probes associated with a gene. As such, the current GEO files do not contain any control probes, although these additional data are available upon request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1552477", "GSM1552478", "GSM1552479", "GSM1552480", "GSM1552481", "GSM1552482", "GSM1552483", "GSM1552484", "GSM1552485", "GSM1552486", "GSM1552487", "GSM1552488", "GSM1552489", "GSM1552490", "GSM1552491", "GSM1552492", "GSM1552493", "GSM1552494", "GSM1552495", "GSM1552496", "GSM1552497", "GSM1552498", "GSM1552499", "GSM1552500", "GSM1552501", "GSM1552502", "GSM1552503", "GSM1552504", "GSM1552505", "GSM1552506", "GSM1552507", "GSM1552508", "GSM1552509", "GSM1552510", "GSM1552511", "GSM1552512", "GSM1552513", "GSM1552514", "GSM1552515", "GSM1552516", "GSM1552517", "GSM1552518", "GSM1552519", "GSM1552520", "GSM1552521", "GSM1552522", "GSM1552523", "GSM1552524", "GSM1552525", "GSM1552526", "GSM1552527", "GSM1552528", "GSM1552529", "GSM1552530", "GSM1552531", "GSM1552532", "GSM1552533", "GSM1552534", "GSM1552535", "GSM1552536", "GSM1552537", "GSM1552538", "GSM1552539", "GSM1552540", "GSM1552541", "GSM1552542", "GSM1552543", "GSM1552544", "GSM1552545", "GSM1552546", "GSM1552547", "GSM1552548", "GSM1552549", "GSM1552550", "GSM1552551", "GSM1552552", "GSM1552553", "GSM1552554", "GSM1552555", "GSM1552556", "GSM1552557", "GSM1552558", "GSM1552559", "GSM1552560", "GSM1552561", "GSM1552562", "GSM1552563", "GSM1552564", "GSM1552565", "GSM1552566", "GSM1552567", "GSM1552568", "GSM1552569", "GSM1552570", "GSM1552571", "GSM1552572", "GSM1552573", "GSM1552574", "GSM1552575", "GSM1552576", "GSM1552577", "GSM1552578", "GSM1552579", "GSM1552580", "GSM1552581", "GSM1552582", "GSM1552583", "GSM1552584", "GSM1552585", "GSM1552586", "GSM1552587", "GSM1552588", "GSM1552589", "GSM1552590", "GSM1552591", "GSM1552592", "GSM1552593", "GSM1552594", "GSM1552595", "GSM1552596", "GSM1552597", "GSM1552598", "GSM1552599", "GSM1552600", "GSM1552601", "GSM1552602", "GSM1552603", "GSM1552604", "GSM1552605", "GSM1552606", "GSM1552607", "GSM1552608", "GSM1552609", "GSM1552610", "GSM1552611", "GSM1552612", "GSM1552613", "GSM1552614", "GSM1552615", "GSM1552616", "GSM1552617", "GSM1552618", "GSM1552619", "GSM1552620", "GSM1552621", "GSM1552622", "GSM1552623", "GSM1552624", "GSM1552625", "GSM1552626", "GSM1552627", "GSM1552628", "GSM1552629", "GSM1552630", "GSM1552631", "GSM1552632", "GSM1552633", "GSM1552634", "GSM1552635", "GSM1552636", "GSM1552637", "GSM1552638", "GSM1552639", "GSM1552640", "GSM1552641", "GSM1552642", "GSM1552643", "GSM1552644", "GSM1552645", "GSM1552646", "GSM1552647", "GSM1552648", "GSM1552649", "GSM1552650", "GSM1552651", "GSM1552652", "GSM1552653", "GSM1552654", "GSM1552655", "GSM1552656", "GSM1552657", "GSM1552658", "GSM1552659", "GSM1552660", "GSM1552661", "GSM1552662", "GSM1552663", "GSM1552664", "GSM1552665", "GSM1552666", "GSM1552667", "GSM1552668"], "sample_count": 192, "group_sizes": null, "group_sizes_basis": null, "platform": "6101", "taxon": "Rattus norvegicus", "title": "Prenatal alcohol exposure alters steady-state and activated gene expression in the adult rat brain", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:26217797:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:8f7233c7f24f6994a4d0702a032becb3f3f85ae943f8e00ecb74c5b9037665dc", "bytes": 1186, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[11]/table-wrap[1]#t0005", "version": null, "note": "Quantile distributions of pairwise Pearson correlations of arrays from the prefrontal cortex (PFC) and hippocampus (HPC).", "structure": {"pmcid": "PMC4510447", "section_index": 11, "section_title": "Data pre-processing and quality control", "row_count": 13, "column_count": 8}, "table": {"label": "Table 1", "caption": "Quantile distributions of pairwise Pearson correlations of arrays from the prefrontal cortex (PFC) and hippocampus (HPC).", "rows": [["Tissue", "Group", "n", "0%", "25%", "50%", "75%", "100%"], ["PFC", "All samples", "96", "0.897", "0.966", "0.971", "0.976", "1.000"], ["Technical replicates", "11", "0.956", "0.972", "0.978", "0.982", "1.000"], ["Amplification replicates", "2", "0.980", "0.980", "0.990", "1.000", "1.000"], ["Hybridization replicates", "9", "0.957", "0.971", "0.979", "0.982", "1.000"], ["Samples only – no outliers", "85", "0.944", "0.968", "0.972", "0.977", "1.000"], ["HPC", "All samples", "96", "0.925", "0.956", "0.965", "0.971", "1.000"], ["Hybridization replicates", "16", "0.936", "0.958", "0.966", "0.973", "1.000"], ["Hybridization Group 1", "4", "0.961", "0.968", "0.971", "0.982", "1.000"], ["Hybridization Group 2", "4", "0.971", "0.972", "0.986", "0.990", "1.000"], ["Hybridization Group 3", "4", "0.964", "0.969", "0.974", "0.984", "1.000"], ["Hybridization Group 4", "4", "0.957", "0.963", "0.980", "0.989", "1.000"], ["Samples only – no outliers", "84", "0.924", "0.958", "0.967", "0.972", "1.000"]], "row_count": 13, "column_count": 8, "numeric_cells": 81, "header_rows": 1, "locator": "section[11]/table-wrap[1]#t0005"}}, {"id": "asset:table:pmid:26217797:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:3c1b9c264bc40fc4e29ce20375b66043180388c801ebf590267f9466584465ba", "bytes": 778, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[11]/table-wrap[2]#t0010", "version": null, "note": "Distribution of sample numbers between different prenatal treatments, termination days, and adjuvant-induced arthritis (AA) treatments for the prefrontal cortex (PFC) and hippocampus (HPC).", "structure": {"pmcid": "PMC4510447", "section_index": 11, "section_title": "Data pre-processing and quality control", "row_count": 14, "column_count": 5}, "table": {"label": "Table 2", "caption": "Distribution of sample numbers between different prenatal treatments, termination days, and adjuvant-induced arthritis (AA) treatments for the prefrontal cortex (PFC) and hippocampus (HPC).", "rows": [["Prenatal treatment", "Termination day", "AA treatment", "PFC", "HPC"], ["Control", "Day 16", "Saline", "5", "5"], ["Adjuvant", "9", "9"], ["Day 39", "Saline", "6", "6"], ["Adjuvant", "8", "8"], ["Pair-fed", "Day 16", "Saline", "5", "5"], ["Adjuvant", "9", "9"], ["Day 39", "Saline", "6", "6"], ["Adjuvant", "9", "7"], ["Prenatal alcohol exposure", "Day 16", "Saline", "5", "5"], ["Adjuvant", "9", "9"], ["Day 39", "Saline", "5", "6"], ["Adjuvant", "9", "9"], ["", "", "Total", "85", "84"]], "row_count": 14, "column_count": 5, "numeric_cells": 32, "header_rows": 1, "locator": "section[11]/table-wrap[2]#t0010"}}, {"id": "asset:table:pmid:26217797:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:f7e0e3db86db4b7658e99533fdaa1f5b4d7dbf441bd97380e2a0aed49867e0d5", "bytes": 546, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[14]/table-wrap[1]#t0015", "version": null, "note": "Total number of variables identified by surrogate variable analysis between steady-state and saline versus adjuvant in the prefrontal cortex (PFC) and hippocampus (HPC).", "structure": {"pmcid": "PMC4510447", "section_index": 14, "section_title": "Differential expression analysis", "row_count": 5, "column_count": 4}, "table": {"label": "Table 3", "caption": "Total number of variables identified by surrogate variable analysis between steady-state and saline versus adjuvant in the prefrontal cortex (PFC) and hippocampus (HPC).", "rows": [["Analysis", "Termination day", "PFC", "HPC"], ["Steady-state (prenatal treatment)", "Day 16", "6", "2"], ["Day 39", "4", "6"], ["Saline versus adjuvant (prenatal treatment ⁎ adjuvant exposure)", "Day 16", "15", "8"], ["Day 39", "11", "12"]], "row_count": 5, "column_count": 4, "numeric_cells": 12, "header_rows": 1, "locator": "section[14]/table-wrap[1]#t0015"}}], "gaps": ["asset:data:geo:GSE63561 not downloaded", "asset:data:geo:GSE63561 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": null, "specific": null, "label": "surrogate variable analysis (sva)", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "In order to correct for these unknown variables, as well as significant batch effects in the two datasets, surrogate variable analysis (sva) was used to generate variables representative of expression heterogeneity within the two datasets [7]."}}], "targets": [{"id": "target-published-estimate", "claim_id": "claim-target-result", "operation": null, "expected_value": 25.0, "unit": "per cent", "tolerance": null, "state": "complete", "note": "The published estimate as the reader quoted it from the paper. No tolerance is published because the paper states none."}], "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": "blocked", "tier": "R4", "blocking_axis": "method", "blocked_on": "method:not_determinable", "axes": {"method": {"tier": "R4", "expressible": false, "required_operations": [], "missing_operations": [], "basis": "The reader quoted the method the paper names (surrogate variable analysis (sva)), but the corpus's method extractor could not map it onto a DSL operation, so the method is published but not expressible."}, "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": ["GSE63561"], "resolved_accessions": ["GSE63561"], "statements": ["Probe-level data for this study were deposited on the GEO (GSE63561), along with metadata describing experimental treatment groups. As described, spatial artifacts were masked from the dataset and data were log 2-transformed prior to submission of raw and quantile-normalized data. Moreover, due to GEO submission requirements, the datasets were filtered to include only probes associated with a gene. As such, the current GEO files do not contain any control probes, although these additional data are available upon request."], "basis": "The paper names GSE63561 in Gene Expression Omnibus (GEO) repository and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:26217797", "data:geo:GSE63561", "asset:table:pmid:26217797:1", "asset:table:pmid:26217797:2", "asset:table:pmid:26217797:3"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE63561"]}, "gaps": ["method:not_determinable"]}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:24:18Z", "independence": "same_provider"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 8, "usage": {"prompt_tokens": 64327, "completion_tokens": 3258, "cached_tokens": 2088}}, "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:26217797", "type": "paper", "label": "pmid:26217797"}, {"id": "source:pmid:26217797", "type": "manuscript", "label": "PMID 26217797 full text"}, {"id": "data:geo:GSE63561", "type": "dataset", "label": "GEO GSE63561"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:26217797", "type": "paper", "label": "pmid:26217797"}, {"id": "source:pmid:26217797", "type": "manuscript", "label": "PMID 26217797 full text"}, {"id": "data:geo:GSE63561", "type": "dataset", "label": "GEO GSE63561"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-26217797", "type": "extraction", "used": ["source:pmid:26217797"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE63561", "type": "accession_resolution", "used": ["data:geo:GSE63561"], "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:26217797", "parent_hash": "sha256:b511f464dd26af3d551b8b41def1f3b989aadea21a00a21d88cb55e93ba9a63a", "fork_of": null, "generation": 5}, "gaps": ["asset:data:geo:GSE63561 licence not read", "asset:data:geo:GSE63561 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"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": ["atal alcohol exposure alters gene expression in the rat brain: Experimental design and bioinformatic", "cohol exposure alters gene expression in the rat brain: Experimental design and bioinformatic", "in the prefrontal cortex and hippocampus of rats prenatally exposed to alcohol under both ste", "., 39, 251-261). In this study, adult female rats from three prenatal treatment groups (ad lib"], "order_basis": "paper_text_order:4", "id": "assay:1"}, {"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": ["imental design and bioinformatic analysis of microarray data.", "ssayed using Illumina׳s RatRef-12 expression microarray. Here, we provide additional metadata, detai", "mental design prior to sample collection and microarray analysis. Adult female rats from one of thre", "terminated 16 or 39 days post-injection and microarray analysis of gene expression was performed on"], "order_basis": "paper_text_order:72", "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":"2026-11-04T02:39:29+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}}}