{"id":"W3097645936","doi":"10.1002/pds.5167","title":"The utility of <scp>real‐world</scp> evidence for benefit‐risk assessment, communication, and evaluation of pharmaceuticals: Case studies","year":2020,"lang":"en","type":"article","venue":"Pharmacoepidemiology and Drug Safety","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Health Canada","funders":"","keywords":"Medicine; Stakeholder; Stakeholder engagement; Risk analysis (engineering); Data collection; Product (mathematics); Brace; Reimbursement; Risk assessment; Health care; Operations management; Engineering; Computer science; Public relations; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2223108,0.0009777141,0.001782638,0.01225049,0.002131952,0.01016024,0.003379862,0.008207515,0.006368852],"category_scores_gemma":[0.4087957,0.0009485729,0.003206071,0.0116891,0.007430247,0.008794421,0.005733053,0.004129161,0.0006938666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009340121,"about_ca_system_score_gemma":0.01114235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002843363,"about_ca_topic_score_gemma":0.006637094,"domain_scores_codex":[0.7069659,0.2338934,0.03239192,0.003372232,0.02190413,0.001472374],"domain_scores_gemma":[0.2225394,0.7268252,0.01972123,0.01468764,0.01525934,0.000967104],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001924127,0.0007777843,0.02533955,0.249838,0.005557147,0.02404908,0.0271853,0.005097328,0.00209667,0.1830731,0.02664994,0.4484118],"study_design_scores_gemma":[0.001044401,0.002302696,0.01156452,0.5392743,0.006374788,0.01984634,0.01824071,0.004476267,0.004855711,0.05980867,0.3319353,0.0002762731],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.09846195,0.6045188,0.07395442,0.0772472,0.002225895,0.01324862,0.002532616,0.0001624464,0.1276482],"genre_scores_gemma":[0.689044,0.1628009,0.1210316,0.01475914,0.0009015158,0.00863451,0.0007653222,0.0001053309,0.001957657],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7776892,"threshold_uncertainty_score":0.9590293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4756097215586652,"score_gpt":0.5926517581892958,"score_spread":0.1170420366306306,"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."}}