{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32133283", "kind": "science-record", "revision": 7, "content_hash": "sha256:74fdc39d9c4607b0b4c49b671916c346fc5ffed5a1726b8c13a0496bb32b8f8d", "created_at": "2026-11-01T15:40:57Z", "updated_at": "2026-11-01T22:01:21Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "The Prognostic Significance of Metabolic Syndrome and a Related Six-lncRNA Signature in Esophageal Squamous Cell Carcinoma.", "doi": "10.3389/fonc.2020.00061", "pmid": "32133283", "authors": ["Yu Liu", "Liyu Wang", "Hengchang Liu", "Chunxiang Li", "Jie He"], "journal": "Frontiers in oncology", "year": 2020, "abstract": "Background: Metabolic syndrome (MetS) is associated with the development of esophageal squamous cell carcinoma (ESCC), and long non-coding RNAs (lncRNAs) are involved in a variety of mechanisms of MetS and tumor. This study will explore the prognostic effect of MetS and the associated lncRNA signature on ESCC. Methods: Our previous RNA-chip data (GSE53624, GSE53622) for 179 ESCC patients were reanalyzed according to MetS. The recurrence-free survival (RFS) was collected for these patients. The status of the MetS-related tumor microenvironment was analyzed with the CIBERSORT and ESTIMATE algorithms. A lncRNA signature was established with univariate and multivariate Cox proportional hazards regression (PHR) analysis and verified using the Kaplan-Meier survival curve analysis and time-dependent receiver operating characteristic (ROC) curves. A clinical predictive model was constructed based on multiple risk factors, evaluated using C-indexes and calibration curves, and verified using data from the GEO and TCGA databases. Results: The results showed that MetS was an independent risk factor for ESCC patients conferring low OS and RFS. Tumor microenvironment analysis indicated that patients with MetS have high stromal scores and M2 macrophage infiltration. A six-lncRNA signature was established by 60 ESCC patients randomly selected from GSE53624 and identified with an effective predictive ability in validation cohorts (59 patients from GSE53624 and 60 patients from GSE53622), subgroup analysis, and ESCC patients from TCGA. MetS and the six-lncRNA signature could be regarded as independent risk factors and enhanced predictive ability in the clinical predictive model. Conclusions: Our results indicated that MetS was associated with poor prognosis in ESCC patients, and the possible mechanism was related to changes in the tumor microenvironment. MetS and the six-lncRNA signature could also serve as independent risk factors with available clinical application value.", "claims": [{"id": "claim-method", "statement": "Next, weighted gene co-expression network analysis (WGCNA) was also used to determine the relationship between the module gene and MetS. Significantly correlated module genes were selected using univariate Cox proportional hazards regression (PHR) analysis to calculate the correlation with OS and RFS. The identified lncRNAs with |z| > 2 were selected, and then, multivariate stepwise Cox PHR analysis was used to build a lncRNA predicting model and identify the best risk score cutoff value to distinguish ESCC patients.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32133283", "locator": "sections[6] \"Identification of lncRNA Signature to Predict the Prognosis for ESCC Patients\" paragraph 2", "quote": "Next, weighted gene co-expression network analysis (WGCNA) was also used to determine the relationship between the module gene and MetS. Significantly correlated module genes were selected using univariate Cox proportional hazards regression (PHR) analysis to calculate the correlation with OS and RFS. The identified lncRNAs with |z| > 2 were selected, and then, multivariate stepwise Cox PHR analysis was used to build a lncRNA predicting model and identify the best risk score cutoff value to distinguish ESCC patients."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data that support the findings of this study come from the public free-charged database, and the new clinical information will be available from the corresponding author, without undue reservation, to any qualified researcher.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32133283", "locator": "sections[19] \"Data Availability Statement\" paragraph 2", "quote": "The data that support the findings of this study come from the public free-charged database, and the new clinical information will be available from the corresponding author, without undue reservation, to any qualified researcher."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "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:32133283"], "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:GSE53622"], "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:GSE53622"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32133283", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2020.00061", "sha256": 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"sha256:9743f153f85b1defaef0ff9e1e108499da17d017ea9be74640b9853379bf163f", "bytes": 2743, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[12]/table-wrap[2]#T2", "version": null, "note": "Association between metabolic syndrome (MetS) and overall survival (OS) in 179 patients in a univariate and multivariable analysis.", "structure": {"pmcid": "PMC7040247", "section_index": 12, "section_title": "Mets Is an Independent Prognostic Factor for ESCC", "row_count": 32, "column_count": 8}, "table": {"label": "Table 2", "caption": "Association between metabolic syndrome (MetS) and overall survival (OS) in 179 patients in a univariate and multivariable analysis.", "rows": [["", "", "", "Univariable", "", "", "Multivariable", ""], ["Variable", "", "Hazard ratio", "95% confidence interval", "p", "Hazard ratio", "95% confidence interval", "p"], ["Age", "<50/50–59", "0.91", "0.46–1.78", "0.776", "0.99", "1.48–2.06", "0.979"], ["", "60–69/50–59", "1.35", "0.87–2.11", "0.185", "1.41", "0.88–2.35", "0.150"], ["", "70–79/50–59", "1.91", "1.01–3.61", "0.047*", "2.08", "1.02–4.25", "0.044*"], ["", ">80/50–59", "5.39", "1.64–17.69", "0.005**", "12.96", "3.62–46.44", "0.0001***"], ["Gender", "Female/male", "1.28", "0.80–2.05", "0.306", "–", "–", "–"], ["Tobacco use", "Yes/no", "0.75", "0.51–1.10", "0.144", "–", "–", "–"], ["Alcohol use", "Yes/no", "0.86", "0.59–1.27", "0.457", "–", "–", "–"], ["Adjuvant therapy", "Yes/no", "1.93", "1.22–3.04", "0.004**", "1.24", "0.74–2.10", "0.413"], ["T stage", "T1/T3", "0.97", "0.44–2.12", "0.935", "1.40", "0.48–4.08", "0.532"], ["", "T2/T3", "1.05", "0.60–1.82", "0.870", "1.26", "0.65–2.45", "0.501"], ["", "T4/T3", "1.64", "1.00–2.67", "0.048*", "1.69", "0.93–3.08", "0.083"], ["N stage", "N1/N0", "2.04", "1.31–3.18", "0.001***", "1.37", "0.68–2.75", "0.379"], ["", "N2/N0", "2.05", "1.14–3.70", "0.017*", "1.20", "0.48–2.97", "0.694"], ["", "N3/N0", "2.97", "1.42–6.19", "0.003**", "1.74", "0.65–4.64", "0.270"], ["TNM stage", "T1/T2", "0.56", "0.17–1.82", "0.336", "0.55", "0.13–2.33", "0.418"], ["", "T3/T2", "2.03", "1.35–3.06", "0.0006***", "1.68", "0.77–3.68", "0.191"], ["Tumor location", "Upper/middle", "1.47", "0.83–2.59", "0.186", "2.03", "1.07–3.86", "0.029*"], ["", "Lower/middle", "0.88", "0.57–1.35", "0.561", "0.66", "0.41–1.07", "0.088"], ["Tumor grade", "Well/moderately", "0.99", "0.57–1.70", "0.961", "1.41", "0.75–2.66", "0.287"], ["", "Poorly/moderately", "1.63", "1.06–2.50", "0.024*", "1.68", "1.05–2.71", "0.032*"], ["MetS", "With/without", "1.73", "1.06–2.82", "0.027*", "2.21", "1.27–3.86", "0.005**"], ["BMI", "Yes/no", "1.30", "0.86–1.96", "0.220", "–", "–", "–"], ["Hyperglycemia", "Yes/no", "1.24", "0.83–1.83", "0.294", "–", "–", "–"], ["Hypertension", "Yes/no", "1.24", "0.83–1.84", "0.290", "–", "–", "–"], ["Triglycerides", "Yes/no", "1.11", "0.65–1.89", "0.701", "–", "–", "–"], ["HDL-C", "Yes/no", "0.95", "0.59–1.54", "0.848", "–", "–", "–"], ["LDL-C", "Yes/no", "1.07", "0.72–1.59", "0.752", "–", "–", "–"], ["Arrhythmia", "Yes/no", "1.12", "0.73–1.72", "0.608", "–", "–", "–"], ["Pneumonia", "Yes/no", "1.43", "0.72–2.83", "0.309", "–", "–", "–"], ["Anastomotic leak", "Yes/no", "1.30", "0.60–2.80", "0.503", "–", "–", "–"]], "row_count": 32, "column_count": 8, "numeric_cells": 150, "header_rows": 2, "locator": "section[12]/table-wrap[2]#T2"}}, {"id": "asset:table:pmid:32133283:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:cb6a34361eaece7d7625d042360cada0a49ac17014d401fc19e6c4b341f29dc9", "bytes": 2756, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[12]/table-wrap[3]#T3", "version": null, "note": "Association between metabolic syndrome (MetS) and recurrence-free survival (RFS) in 179 patients in a univariate and multivariable analysis.", "structure": {"pmcid": "PMC7040247", "section_index": 12, "section_title": "Mets Is an Independent Prognostic Factor for ESCC", "row_count": 32, "column_count": 8}, "table": {"label": "Table 3", "caption": "Association between metabolic syndrome (MetS) and recurrence-free survival (RFS) in 179 patients in a univariate and multivariable analysis.", "rows": [["", "", "", "Univariable", "", "", "Multivariable", ""], ["Variable", "", "Hazard ratio", "95% confidence interval", "p", "Hazard ratio", "95% confidence interval", "p"], ["Age", "<50/50–59", "1.36", "0.74–2.51", "0.325", "1.83", "0.90–3.70", "0.094"], ["", "60–69/50–59", "0.75", "0.45–1.26", "0.283", "0.83", "0.46–1.48", "0.525"], ["", "70–79/50–59", "0.97", "0.43–2.21", "0.947", "1.06", "0.43–2.62", "0.892"], ["", ">80/50–59", "1.13", "0.15–8.32", "0.901", "2.25", "0.28–17.89", "0.445"], ["Gender", "Female/male", "0.75", "0.41–1.39", "0.359", "–", "–", "–"], ["Tobacco use", "Yes/no", "1.18", "0.74–1.88", "0.492", "–", "–", "–"], ["Alcohol use", "Yes/no", "1.31", "0.83–2.06", "0.247", "–", "–", "–"], ["Adjuvant therapy", "Yes/no", "8.50", "3.69–19.55", "0.0001***", "5.34", "2.23–12.77", "0.0002***"], ["T stage", "T1/T3", "1.13", "0.48–2.65", "0.776", "1.18", "0.36–3.82", "0.787"], ["", "T2/T3", "0.80", "0.39–1.64", "0.548", "1.03", "0.44–2.39", "0.946"], ["", "T4/T3", "2.38", "1.41–4.04", "0.001**", "1.40", "0.74–2.64", "0.303"], ["N stage", "N1/N0", "2.51", "1.47–4.29", "0.0001***", "1.03", "0.45–2.35", "0.940"], ["", "N2/N0", "3.26", "1.67–6.39", "0.0001***", "1.11", "0.41–2.99", "0.833"], ["", "N3/N0", "6.56", "3.08–14.00", "0.0001***", "2.21", "0.74–6.61", "0.156"], ["TNM stage", "T1/T2", "1.15", "0.34–3.89", "0.822", "1.18", "0.28–5.02", "0.824"], ["", "T3/T2", "3.67", "2.18–6.18", "0.0001***", "2.72", "1.12–6.61", "0.027*"], ["Tumor location", "Upper/middle", "1.50", "0.79–2.83", "0.217", "1.37", "0.65–2.86", "0.406"], ["", "Lower/middle", "0.85", "0.52–1.39", "0.513", "0.58", "0.34–1.00", "0.051"], ["Tumor grade", "Well/moderately", "0.76", "0.39–1.46", "0.403", "1.02", "0.47–2.21", "0.959"], ["", "Poorly/moderately", "1.00", "0.60–1.66", "0.989", "0.86", "0.49–1.51", "0.597"], ["MetS", "With/without", "1.71", "0.99–2.96", "0.055", "2.39", "1.29–4.43", "0.005**"], ["BMI", "Yes/no", "1.24", "0.77–2.00", "0.373", "–", "–", "–"], ["Hyperglycemia", "Yes/no", "1.58", "1.02–2.46", "0.040*", "–", "–", "–"], ["Hypertension", "Yes/no", "1.14", "0.72–1.79", "0.574", "–", "–", "–"], ["Triglycerides", "Yes/no", "1.04", "0.57–1.93", "0.888", "–", "–", "–"], ["HDL-C", "Yes/no", "0.68", "0.38–1.24", "0.211", "–", "–", "–"], ["LDL-C", "Yes/no", "0.93", "0.59–1.48", "0.759", "–", "–", "–"], ["Arrhythmia", "Yes/no", "0.99", "0.59–1.66", "0.981", "–", "–", "–"], ["Pneumonia", "Yes/no", "1.10", "0.48–2.53", "0.821", "–", "–", "–"], ["Anastomotic leak", "Yes/no", "1.03", "0.42–2.54", "0.952", "–", "–", "–"]], "row_count": 32, "column_count": 8, "numeric_cells": 150, "header_rows": 2, "locator": "section[12]/table-wrap[3]#T3"}}, {"id": "asset:table:pmid:32133283:4", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:eb277250bb3200fdfe6eabfe83a81829433accb02c2c9b54229414fc2bbc410d", "bytes": 1200, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[16]/table-wrap[1]#T4", "version": null, "note": "The multivariable analysis for MetS and six-lncRNA signature.", "structure": {"pmcid": "PMC7040247", "section_index": 16, "section_title": "The Six-lncRNA Signature Is an Independent Risk Factor", "row_count": 11, "column_count": 8}, "table": {"label": "Table 4", "caption": "The multivariable analysis for MetS and six-lncRNA signature.", "rows": [["Group", "Factors", "Overall survival (OS)", "Recurrence-free survival (RFS)"], ["", "", "HR", "95% CI", "p", "HR", "95% CI", "p"], ["60 patients(training)", "MetS", "4.26", "1.13–16.03", "0.031*", "5.87", "1.20–28.62", "0.028*"], ["", "Six-lncRNA signature", "3.49", "1.57–7.77", "0.002**", "5.27", "1.56–17.75", "0.007**"], ["59 patients (validation 1)", "MetS", "9.82", "1.96–49.10", "0.005**", "84.26", "5.67–1253.30", "0.001**"], ["", "Six-lncRNA signature", "7.21", "2.02–25.76", "0.002**", "104.03", "7.90–1370.66", "0.0004***"], ["60 patients (validation 2)", "MetS", "2.38", "0.75–7.54", "0.141", "1.32", "0.42–4.16", "0.635"], ["", "Six-lncRNA signature", "3.00", "1.18–7.62", "0.02*", "3.37", "0.96–11.81", "0.058"], ["Total 179 patients", "MetS", "2.67", "1.48–4.83", "0.001**", "2.40", "1.25–4.60", "0.008**"], ["", "Six-lncRNA signature", "3.97", "2.47–6.36", "0.0001***", "3.23", "1.95–5.35", "0.0001***"], ["80 patients from TCGA", "Six-lncRNA signature", "5.37", "1.02–28.41", "0.047*", "3.47", "1.04–11.62", "0.043*"]], "row_count": 11, "column_count": 8, "numeric_cells": 61, "header_rows": 2, "locator": "section[16]/table-wrap[1]#T4"}}], "gaps": ["asset:data:geo:GSE53622 not downloaded", "asset:data:geo:GSE53622 licence not read", "asset:data:geo:GSE53624 not downloaded", "asset:data:geo:GSE53624 licence not read"]}, "analysis": {"state": "complete", "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": "verbatim", "quote": "Next, weighted gene co-expression network analysis (WGCNA) was also used to determine the relationship between the module gene and MetS. Significantly correlated module genes were selected using univariate Cox proportional hazards regression (PHR) analysis to calculate the correlation with OS and RFS. The identified lncRNAs with |z| > 2 were selected, and then, multivariate stepwise Cox PHR analysis was used to build a lncRNA predicting model and identify the best risk score cutoff value to distinguish ESCC patients."}}, {"id": "method-2", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Kaplan-Meier"}}, {"id": "method-3", "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": "log-rank"}}, {"id": "method-4", "family": "differential_expression", "specific": "edger", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 0.8, "band": "high", "quote": "edgeR"}}, {"id": "method-5", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 0.8, "band": "high", "quote": "limma"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["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": ["GSE53624", "GSE53622"], "resolved_accessions": ["GSE53624", "GSE53622"], "statements": ["The data that support the findings of this study come from the public free-charged database, and the new clinical information will be available from the corresponding author, without undue reservation, to any qualified researcher."], "basis": "The paper names GSE53624, GSE53622 in GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["cox_ph"], "assets": ["source:pmid:32133283", "data:geo:GSE53622", "asset:table:pmid:32133283:1", "asset:table:pmid:32133283:2", "asset:table:pmid:32133283:3", "asset:table:pmid:32133283:4"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE53622"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:18:37Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 3, "usage": {"prompt_tokens": 23205, "completion_tokens": 2162, "cached_tokens": 784}}, "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:32133283", "type": "paper", "label": "pmid:32133283"}, {"id": "source:pmid:32133283", "type": "manuscript", "label": "PMID 32133283 full text"}, {"id": "data:geo:GSE53622", "type": "dataset", "label": "GEO GSE53622"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:32133283", "type": "paper", "label": "pmid:32133283"}, {"id": "source:pmid:32133283", "type": "manuscript", "label": "PMID 32133283 full text"}, {"id": "data:geo:GSE53622", "type": "dataset", "label": "GEO GSE53622"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-32133283", "type": "extraction", "used": ["source:pmid:32133283"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE53622", "type": "accession_resolution", "used": ["data:geo:GSE53622"], "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:32133283", "parent_hash": "sha256:8522b0ad057e4de5bd4bfab65be07910fd4bbed89ddd2044c4cf270a7c893225", "fork_of": null, "generation": 6}, "gaps": ["asset:data:geo:GSE53622 licence not read", "asset:data:geo:GSE53622 not downloaded", "asset:data:geo:GSE53624 licence not read", "asset:data:geo:GSE53624 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"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": ["Next, weighted gene co-expression network analysis (WGCNA) was also used to determine the relationship between the module gene and MetS. Significantly correlated module genes were selected using univariate Cox proportional hazards regression (PHR) analysis to calculate the correlation with OS and RFS. The identified lncRNAs with |z| > 2 were selected, and then, multivariate stepwise Cox PHR analysis was used to build a lncRNA predicting model and identify the best risk score cutoff value to distinguish ESCC patients."], "order_basis": "analysis_only", "id": "assay:1"}]},"meta":{"api_version":"v1","automation_ladder_snapshot":"ba34b49490d9bfaf","automation_ladder_caveats":["Method extraction is rule-based and has no hand-judged accuracy sample. Evidence bands order textual support; method agreement intervals are null (n=0), never probabilities. Work-type validation does not validate methods.","Operation coverage describes only explicitly named methods. It does not prove a complete protocol, compatible parameters, successful compilation or re-execution. Unrecognised or ambiguous methods require review.","Data reachability is a textual accession or public-data statement. No dataset was downloaded or checked for access, completeness or licence.","Capabilities are planning states seeded from the dated equipment register. No bench ownership, completed quote or partner booking is inferred. Procurement counts are dependencies, not guaranteed replications or financial returns.","Tier and blocker counts are deterministic assessments of this corpus, not measured agreement. R3 is reserved for procurement; unresolved methods and data require human work (R4). The most restrictive axis wins, with capability, method, data as tie-breaks. Resolving one blocker can leave another at the same tier."],"engine":"corpus_engine","engine_provider":"rule_based_v1+lex99e1195c7d6f","run_id":"run-20261023T122449232913","source":"esearch","source_detail":"PubMed mirror biomed_pubmed (read-only)","run_status":"complete","imported_at":"2026-11-03T20:16:52+00:00","generated_at":"2026-11-04T02:15:06+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}}}