Construction and validation of a prognostic model based on anoikis-fatty acid metabolism-related genes in colorectal cancer: A retrospective cohort study.

{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41496025", "kind": "science-record", "revision": 2, "content_hash": "sha256:607f51e08c22c3b7e5f6b2d5e50d836fdec2d2c95728877937ce41cfe96779b9", "created_at": "2026-11-01T10:25:54Z", "updated_at": "2026-11-01T14:01:53Z", "generator": {"name": "corpus-assay-engine", "converter": "sep_to_sci_v1", "source_package_schema": "urn:bntrg:sep:1.0.0"}, "paper": {"state": "partial", "title": "Construction and validation of a prognostic model based on anoikis-fatty acid metabolism-related genes in colorectal cancer: A retrospective cohort study.", "doi": "10.1097/md.0000000000046863", "pmid": "41496025", "authors": null, "journal": "Medicine", "year": 2026, "abstract": null, "claims": [{"id": "claim-1", "statement": "the headline numerical result the paper states for its main finding", "kind": "qualitative", "state": "blocked", "target": {"value": null, "unit": null, "tolerance": null, "source": null}, "evidence": []}], "gaps": ["abstract", "authors"]}, "experiment": {"state": "partial", "objective": "the headline numerical result the paper states for its main finding", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate and its interval from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The number a replication must land on, and the sentence it came from.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:41496025"], "outputs": ["the published estimate, its unit and its interval"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data behind the published result", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:not_downloaded", "description": "The published result cannot be recomputed without the data the paper analysed.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the source data with its provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the analysis programme", "kind": "analysis", "state": "blocked", "blocked_on": "no owned computational capability is bound to this experiment", "description": "Re-run the paper's analysis on the source data and produce the registered result. | SEP input not carried into the asset list: materials:the source data behind the published result in pmid:41496025", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the registered result"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:not_downloaded", "step:run_analysis blocked on no owned computational capability is bound to this experiment", "step:run_analysis input 'materials:the source data behind the published result in pmid:41496025' does not resolve to a declared asset"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:41496025", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1097/md.0000000000046863", "sha256": "sha256:cf600883ee67f71fcbfdc6f75d6ed5b500b423d5eb27670126789fcf5454122d", "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1097/md.0000000000046863", "version": null, "note": "Source read by the package builder: full_text.", "structure": {"access_state": "full_text"}}, {"id": "asset:table:pmid:41496025:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:f2c9a3188011c60a987dcc4a301c529b36e9c9c9e40a39231ec4b931ad7268c4", "bytes": 1427, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[15]/table-wrap[1]#T1", "version": null, "note": "The clinicopathological features in the training and testing sets.", "structure": {"pmcid": "PMC12778156", "section_index": 15, "section_title": "3.4. Construction and validation of prognostic models based on AFRGs", "row_count": 22, "column_count": 6}, "table": {"label": "Table 1", "caption": "The clinicopathological features in the training and testing sets.", "rows": [["Covariates", "Type", "Total", "Test", "Train", "P-value"], ["Age", "≤65", "270 (43.55%)", "76 (40.86%)", "194 (44.7%)", ".4264"], [">65", "350 (56.45%)", "110 (59.14%)", "240 (55.3%)"], ["Gender", "Female", "291 (46.94%)", "83 (44.62%)", "208 (47.93%)", ".5046"], ["Male", "329 (53.06%)", "103 (55.38%)", "226 (52.07%)"], ["Stage", "Stage I", "105 (16.94%)", "34 (18.28%)", "71 (16.36%)", ".3952"], ["Stage II", "227 (36.61%)", "68 (36.56%)", "159 (36.64%)"], ["Stage III", "179 (28.87%)", "57 (30.65%)", "122 (28.11%)"], ["Stage IV", "89 (14.35%)", "20 (10.75%)", "69 (15.9%)"], ["unknown", "20 (3.23%)", "7 (3.76%)", "13 (3%)"], ["T", "T1", "20 (3.23%)", "4 (2.15%)", "16 (3.69%)", ".5155"], ["T2", "105 (16.94%)", "35 (18.82%)", "70 (16.13%)"], ["T3", "423 (68.23%)", "123 (66.13%)", "300 (69.12%)"], ["T4", "70 (11.29%)", "24 (12.9%)", "46 (10.6%)"], ["unknown", "2 (0.32%)", "0 (0%)", "2 (0.46%)"], ["M", "M0", "459 (74.03%)", "142 (76.34%)", "317 (73.04%)", ".1021"], ["M1", "88 (14.19%)", "19 (10.22%)", "69 (15.9%)"], ["unknown", "73 (11.77%)", "25 (13.44%)", "48 (11.06%)"], ["N", "N0", "351 (56.61%)", "107 (57.53%)", "244 (56.22%)", ".7865"], ["N1", "150 (24.19%)", "47 (25.27%)", "103 (23.73%)"], ["N2", "116 (18.71%)", "32 (17.2%)", "84 (19.35%)"], ["unknow", "3 (0.48%)", "0 (0%)", "3 (0.69%)"]], "row_count": 22, "column_count": 6, "numeric_cells": 71, "header_rows": 1, "locator": "section[15]/table-wrap[1]#T1"}}], "gaps": ["asset:source:pmid:41496025 not verified"]}, "analysis": {"state": "absent", "methods": [], "targets": [], "gaps": ["method", "targets"]}, "capability": {"state": "absent", "requirements": [], "gaps": ["capability"]}, "readiness": {"state": "partial", "tier": null, "blocking_axis": null, "blocked_on": null, "axes": {}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:41496025", "asset:table:pmid:41496025:1"], "steps": ["read_published_estimate"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:41496025"]}, "gaps": ["corpus_record_absent"]}, "review": {"state": "partial", "machine_critique": {"status": "blocked", "providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "full-text-reading-v1", "prompt_hash": "e763144baead03ccf7b6e5a1eb95b00e046f169128d85e97d39bc15de13b3554", "source_hash": "cf600883ee67f71fcbfdc6f75d6ed5b500b423d5eb27670126789fcf5454122d", "raw_response_sha256": "sha256:bfe491adf5e81e675b32c74e85c257f8537bc7bc961ce5bdf1e322ea1176bdb0", "raw_response_chars": 4574}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "f7acb1fac5ec065a026cdfd0469a0dd5000cc7dd9b6a90ed2290aa8c1f828f58", "source_hash": "cf600883ee67f71fcbfdc6f75d6ed5b500b423d5eb27670126789fcf5454122d", "raw_response_sha256": "sha256:d6329de15a9d0120620e2c8385f1c3ed5b549470e26a1230bfee529efaad0888", "raw_response_chars": 46932}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "431876e9608144a0ba2ce33905d0515d933fd4a47edad9b7a98261dc102c5e5a", "source_hash": "cf600883ee67f71fcbfdc6f75d6ed5b500b423d5eb27670126789fcf5454122d", "raw_response": "{\"parent_value\":0.889,\"unit\":\"area under the curve (AUC)\",\"evidence\":\"(e.g., the 1-year OS AUC of 0.889 in GSE12945 might not be fully reproducible in larger independent cohorts)\",\"target_result\":\"The 1-year overall survival AUC in the GSE12945 external validation cohort.\",\"number_stated\":true}", "reading": {"parent_value": 0.889, "unit": "area under the curve (AUC)", "evidence": "(e.g., the 1-year OS AUC of 0.889 in GSE12945 might not be fully reproducible in larger independent cohorts)", "target_result": "The 1-year overall survival AUC in the GSE12945 external validation cohort.", "number_stated": true, "source_locator": "chars 6222-6330 of source sha256 cf600883ee67f71fcbfdc6f75d6ed5b500b423d5eb27670126789fcf5454122d"}, "recorded_at": "2026-10-31T15:26:25.864491+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "cd90a5d31f058ebcaf32282b2c3e3ab34d693801dfefd6e96e54d245787ec764", "source_hash": "cf600883ee67f71fcbfdc6f75d6ed5b500b423d5eb27670126789fcf5454122d", "raw_response": "<think>We need answer JSON object only. Need identify single numerical result replication registered target headline numerical result paper states for main finding. Ambiguity: headline result could external validation AUC perhaps 1-year OS AUC 0.889, explicitly singled in limitations \"the 1-year OS AUC of 0.889 in GSE12945 might not be fully reproducible\". User asks \"find the single numerical result that a replication of the registered target has to reproduce. Report headline number only: value paper itself states for registered target, not calculated... Registered target: headline numerical result the paper states for its main finding.\" Need infer intended likely 0.889? They emphasize single numerical result replication. Main finding in abstract: 1-,3-,5-year OS AUC 0.889/0.795/0.740. That's three values, but asks single numerical result. Conclusion specifically flags 1-year OS AUC 0.889 might not be fully reproducible. Maybe expected number is 0.889 with unit \"AUC\". Evidence exact contiguous quote containing number and attribution whole clause. Need target_result wording.\n\nCould headline numerical result perhaps n=62? No, main finding likely prognostic model, and the prominent headline number is AUC. The question likely generated task to extract \"parent_value\" from paper, perhaps asks numerical result for \"registered target\" abstract. Registered target generic. Need pick one single. The conclusion's wording \"e.g., the 1-year OS AUC of 0.889 in GSE12945 might not be fully reproducible...\" explicitly frames reproducibility, likely strongest clue. Quote whole clause maybe \"the 1-year OS AUC of 0.889 in GSE12945 might not be fully reproducible in larger independent cohorts\". Exact contiguous. Unit should printed: likely \"AUC\" (unitless but paper prints AUC). parent_value 0.889. target_result perhaps \"The 1-year overall survival AUC in GSE12945 was 0.889.\" Evidence exact quote. Need not include full sentence? Requirement exact contiguous quotation, no shorten; can quote clause. \"the 1-year OS AUC of 0.889 in GSE12945 might not be fully reproducible in larger independent cohorts\" is exact. Parent target result says what. JSON valid.\n\nCheck whether they perhaps expect 0.889/0.795/0.740 but parent_value must number, single numerical result. \"headline number only\" likely 0.889. Could be AUC as unit. The phrase \"registered target\" perhaps benchmark asks extract \"parent_value\" corresponding to some question, but registered target intentionally generic. Main finding headline numerical result maybe \"1-year OS AUC: 0.889/0.795/0.740\" and first is headline. They may expect 0.889.\n\nNeed ensure evidence attribution names target directly. Quote full clause includes GSE12945 and 1-year OS AUC. Good.\n\ntarget_result maybe \"The paper reports a 1-year overall survival AUC of 0.889 in GSE12945.\" This is paraphrase but allowed target_result. Unit \"AUC\" paper prints. Could unit be \"area under the curve (AUC)\"? They say unit must unit paper prints. Since AUC is metric, perhaps unit \"AUC\". Use exact printed term \"AUC\".\n\nReturn JSON only, no markdown.</think>\n\n{\"parent_value\":0.889,\"unit\":\"AUC\",\"evidence\":\"the 1-year OS AUC of 0.889 in GSE12945 might not be fully reproducible in larger independent cohorts\",\"target_result\":\"The paper reports a 1-year overall survival AUC of 0.889 in GSE12945.\",\"number_stated\":true}", "reading": {"parent_value": 0.889, "unit": "AUC", "evidence": "the 1-year OS AUC of 0.889 in GSE12945 might not be fully reproducible in larger independent cohorts", "target_result": "The paper reports a 1-year overall survival AUC of 0.889 in GSE12945.", "number_stated": true, "source_locator": "chars 6229-6329 of source sha256 cf600883ee67f71fcbfdc6f75d6ed5b500b423d5eb27670126789fcf5454122d"}, "recorded_at": "2026-10-31T15:26:28.763083+00:00"}], "agreement": false, "disagreements": {"target_result": {"minimax": "The 5-gene prognostic model had 1-, 3-, and 5-year overall survival AUC values of 0.889, 0.795, and 0.740, respectively, in GSE12945.", "minimax_alt": "A 5-gene (BRCA1, CD36, ENO3, INHBB, PHLDA2) model showed robust predictive efficacy (1-, 3-, 5-year OS area under the curve: 0.889/0.795/0.740 in GSE12945).", "decisive": false}, "analysis_methods": {"minimax": ["Differential expression analysis using the Limma package", "ComBat batch-effect correction using the sva package", "Non-negative matrix factorization clustering", "Univariate Cox regression", "LASSO regression with cross-validation", "Multivariate Cox modeling", "Receiver operating characteristic curve analysis using the pROC roc function", "Area under the curve and confidence interval calculation using the pROC CI function", "Nomogram analysis", "Kaplan–Meier curve analysis", "Log-rank test"], "minimax_alt": ["Differential expression analysis using the Limma package", "ComBat batch-effect correction using the sva package", "NMF clustering", "Univariate Cox regression", "LASSO regression with cross-validation", "Multivariate Cox model for risk-score construction", "Receiver operating characteristic curve analysis and area under the curve estimation using the pROC package", "Nomogram", "Immune infiltration analysis", "Kaplan–Meier Curve analysis and log-rank test"], "decisive": false}, "statistical_method": {"minimax": "Receiver operating characteristic (ROC) curve analysis, with AUC values and confidence intervals calculated using the roc and CI functions in the pROC package", "minimax_alt": "Receiver operating characteristic (ROC) curve analysis with area under the curve (AUC) estimation", "decisive": true}, "unit": {"minimax": "area under the curve (AUC)", "minimax_alt": "AUC", "decisive": true}}, "agreement_basis": {"policy": "decisive_fields", "decisive_fields": ["work_type", "number_stated", "parent_value", "unit"]}, "blinded": true}, "human_critique": {"status": "not_run", "reviewer": null, "signed_at": null, "conflict_checked": false, "commentary": null}, "stages": [{"key": "target_materials", "status": "pending", "reason": null, "evidence": null}, {"key": "independent_readings", "status": "blocked", "reason": "The independent readings are incomplete or disagree; the source evidence must resolve the difference.", "evidence": {"provider_errors": []}}, {"key": "source_resolution", "status": "pending", "reason": null, "evidence": null}, {"key": "protocol_reconstruction", "status": "pending", "reason": null, "evidence": null}, {"key": "control_execution", "status": "pending", "reason": null, "evidence": null}, {"key": "control_comparison", "status": "pending", "reason": null, "evidence": null}, {"key": "publication", "status": "pending", "reason": null, "evidence": null}], "gaps": ["review.human_critique", "review.machine_critique.blocked"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "package:d274b147281d80d024a3f73ce7445ec3f251834c0b127d5888403162b32c233e", "type": "sep_package", "label": "SEP v1 package for pmid:41496025"}], "activities": [{"id": "activity:conversion:pmid:41496025", "type": "conversion", "used": ["package:d274b147281d80d024a3f73ce7445ec3f251834c0b127d5888403162b32c233e"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:minimax", "type": "model", "label": "minimax"}, {"id": "agent:minimax_alt", "type": "model", "label": "minimax_alt"}, {"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}], "source_run_id": "run-20261023T122449232913", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:41496025", "parent_hash": "sha256:4bfc4b5898f668c8190841c3fc86200578f633a947e20ca319b02fabfe810e66", "fork_of": null, "generation": 2}, "gaps": ["abstract", "asset:source:pmid:41496025 not verified", "authors", "capability", "corpus_record_absent", "execution.not_run", "method", "review.human_critique", "review.machine_critique.blocked", "step:obtain_source_data blocked on data:not_downloaded", "step:run_analysis blocked on no owned computational capability is bound to this experiment", "step:run_analysis input 'materials:the source data behind the published result in pmid:41496025' does not resolve to a declared asset", "targets"]}