{"id":"W1819504360","doi":"10.1002/pds.2316","title":"Design considerations in an active medical product safety monitoring system","year":2012,"lang":"en","type":"article","venue":"Pharmacoepidemiology and Drug Safety","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Ministry of Health","funders":"Hamilton Health Sciences Foundation; U.S. Department of Health and Human Services","keywords":"Confounding; Medicine; Spurious relationship; Observational study; Cohort; Cohort study; Product (mathematics); Risk analysis (engineering); Econometrics; Computer science; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.08696198,0.0008325775,0.001058251,0.0007259169,0.001218693,0.003837887,0.003363774,0.00448951,0.01106206],"category_scores_gemma":[0.09080209,0.0009378015,0.001407456,0.000599481,0.001506004,0.002965468,0.002214775,0.00255568,0.002716027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002121505,"about_ca_system_score_gemma":0.004787818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001058438,"about_ca_topic_score_gemma":0.001228593,"domain_scores_codex":[0.9212132,0.06562958,0.003020214,0.002295083,0.006898465,0.0009434822],"domain_scores_gemma":[0.9099309,0.06871925,0.004152954,0.006067056,0.009215915,0.001913897],"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":[0.01445168,0.004450716,0.02671872,0.01012045,0.001175742,0.001763582,0.005974053,0.06737095,0.01824665,0.2655272,0.03348181,0.5507184],"study_design_scores_gemma":[0.01072059,0.05919287,0.028428,0.006107125,0.001919002,0.002789474,0.003389455,0.09062752,0.0200172,0.1941721,0.5820917,0.000544881],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0797325,0.003508899,0.7960061,0.04021421,0.002456537,0.03379098,0.001475747,0.001762881,0.04105213],"genre_scores_gemma":[0.2027765,0.001156649,0.7418005,0.01153189,0.0008553584,0.03323114,0.0004031428,0.0001788995,0.008065924],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.08696198,"threshold_uncertainty_score":0.4599044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5846020368607875,"score_gpt":0.5885438474925444,"score_spread":0.003941810631756915,"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."}}