{"id":"W4390298060","doi":"10.1002/pds.5746","title":"Assessing cumulative effects of medication use: New insights and new challenges","year":2023,"lang":"en","type":"article","venue":"Pharmacoepidemiology and Drug Safety","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Spurious relationship; Pharmacoepidemiology; Covariate; Cumulative incidence; Econometrics; Cumulative effects; Intensive care medicine; Actuarial science; Pharmacology; Statistics; Cohort; Internal medicine; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.005709264,0.0001810688,0.00085296,0.00009387586,0.00009102824,0.000008303375,0.0001033814,0.0001824906,0.00003478363],"category_scores_gemma":[0.1646978,0.0001415316,0.00005856497,0.0001582333,0.0002757694,0.0001995867,0.0001429833,0.0003092415,0.000007470512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001377289,"about_ca_system_score_gemma":0.00006587074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000590352,"about_ca_topic_score_gemma":0.00000586134,"domain_scores_codex":[0.9946546,0.003671715,0.0008850298,0.0004041473,0.0001363169,0.000248204],"domain_scores_gemma":[0.722482,0.2766874,0.000368087,0.0001672352,0.00003912802,0.0002562094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003685812,0.0001030926,0.003251635,0.001397549,0.0004278621,0.00002324347,0.0042899,0.00001516628,0.00169031,0.4479081,0.03178642,0.5087381],"study_design_scores_gemma":[0.001668198,0.00004211071,0.0407789,0.0002074584,0.0001996695,0.000003346455,0.00008430704,0.00191705,0.001177888,0.9512922,0.002478895,0.0001499657],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.338384,0.01917998,0.5818292,0.05100887,0.003980442,0.002350637,0.00003680382,0.0007592762,0.002470822],"genre_scores_gemma":[0.3704962,0.03724482,0.5894477,0.001234187,0.0009369798,0.00002418611,0.000009413199,0.00005032301,0.0005561965],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5085881,"threshold_uncertainty_score":0.8423383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6520777044900588,"score_gpt":0.6033826546866505,"score_spread":0.04869504980340822,"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."}}