{"id":"W4404021068","doi":"10.1097/ede.0000000000001808","title":"A Structural Description of Biases That Generate Immortal Time","year":2024,"lang":"en","type":"article","venue":"Epidemiology","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital","funders":"National Institute of Allergy and Infectious Diseases; National Institutes of Health; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Medical Research Council; National Institute for Health and Care Research","keywords":"Selection (genetic algorithm); Computer science; Emulation; Selection bias; Term (time); Observational study; Statistics; Artificial intelligence; Psychology; Mathematics; Social psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.0008204294,0.00014124,0.0004414079,0.0001019537,0.0000256738,0.00000568207,0.0001197396,0.0001348193,0.0004188566],"category_scores_gemma":[0.003409729,0.0001077039,0.000101659,0.000103181,0.0001492543,0.0001564803,0.0000552693,0.0001680835,0.00004114766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004666184,"about_ca_system_score_gemma":0.00002426575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003866108,"about_ca_topic_score_gemma":0.00001106291,"domain_scores_codex":[0.9987405,0.0002945926,0.0004240525,0.0002369992,0.00005860281,0.0002452727],"domain_scores_gemma":[0.9963788,0.003170946,0.0001341143,0.0002361584,0.00003785317,0.00004212098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004928289,0.00003290687,0.008411828,0.0003296949,0.0001976609,0.00006147545,0.0004798308,0.0002847136,0.1056928,0.8188908,0.04870947,0.01685956],"study_design_scores_gemma":[0.00004875512,0.0001115262,0.001256559,0.0001082714,0.00003365823,0.00006222118,0.00001707071,0.02957711,0.01219194,0.956092,0.0003580493,0.0001428662],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9411896,0.001383735,0.05503267,0.0004130242,0.0003059657,0.0001840039,0.00003275332,0.0005506527,0.0009075486],"genre_scores_gemma":[0.9264474,0.00005069304,0.07251082,0.0001428137,0.0001284023,0.00002311741,0.00002577545,0.00002301541,0.0006479583],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1372012,"threshold_uncertainty_score":0.4586186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5136780440079687,"score_gpt":0.4768538274050714,"score_spread":0.03682421660289725,"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."}}