{"id":"W4383186980","doi":"10.1186/s12874-023-01978-6","title":"Effect of alcohol consumption on breast cancer: probabilistic bias analysis for adjustment of exposure misclassification bias and confounders","year":2023,"lang":"en","type":"article","venue":"BMC Medical Research Methodology","topic":"Cancer Risks and Factors","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Tehran University of Medical Sciences and Health Services","keywords":"Confounding; Medicine; Breast cancer; Odds ratio; Population; Logistic regression; Information bias; Statistics; Attributable risk; Alcohol consumption; Cancer; Selection bias; Mathematics; Alcohol; Internal medicine; Environmental health; Pathology; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0194154,0.0001291209,0.0008535784,0.0007715093,0.00005558179,0.000004766744,0.0001179938,0.0002501744,0.0003851392],"category_scores_gemma":[0.03170533,0.00008934896,0.0001991672,0.0009251926,0.0009241974,0.00001715121,0.00005539542,0.0003061868,0.000004513126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001392706,"about_ca_system_score_gemma":0.0006707322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001447466,"about_ca_topic_score_gemma":0.00104488,"domain_scores_codex":[0.9931219,0.004491617,0.0005133261,0.0004070358,0.001094846,0.0003713137],"domain_scores_gemma":[0.9551652,0.04368071,0.0001694342,0.0003151485,0.0003542786,0.0003152216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01266469,0.0002408566,0.7441463,0.008299478,0.001363261,0.000009351241,0.0005751341,0.0002551037,0.009652544,0.002812716,0.001513469,0.218467],"study_design_scores_gemma":[0.004935618,0.004060037,0.9748297,0.0004762127,0.0009757613,0.00001428494,0.0002792864,0.009191739,0.004473638,0.0003535941,0.0003034086,0.0001067461],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902783,0.0006301792,0.006209388,0.001145079,0.0001486341,0.001403007,0.0001176766,0.00002572119,0.00004198733],"genre_scores_gemma":[0.99518,0.002971212,0.0009663377,0.00004090659,0.0001144767,0.0004614038,0.00009989166,0.00001593637,0.0001498262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2306833,"threshold_uncertainty_score":0.976451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6737063483700801,"score_gpt":0.5808430157274987,"score_spread":0.0928633326425814,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}