{"id":"W4389205459","doi":"10.3389/fmed.2023.1299239","title":"Quality and quantity of data used by Health Canada in approving new drugs","year":2023,"lang":"en","type":"article","venue":"Frontiers in Medicine","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Toronto","funders":"","keywords":"Medicine; Clinical trial; Orphan drug; Demographics; Drug; Family medicine; Alternative medicine; Internal medicine; Pharmacology; Demography; Pathology; Bioinformatics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.5436204,0.0006311688,0.001663043,0.01800602,0.003393142,0.0150145,0.004674423,0.002308088,0.001836522],"category_scores_gemma":[0.7817476,0.00162274,0.002720909,0.02640076,0.005979489,0.006057232,0.006177581,0.00384616,0.0003686589],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06431515,"about_ca_system_score_gemma":0.1218594,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5062962,"about_ca_topic_score_gemma":0.4686985,"domain_scores_codex":[0.2162187,0.3860399,0.105859,0.01476628,0.2705635,0.00655262],"domain_scores_gemma":[0.04561433,0.5473533,0.1809451,0.0436381,0.1769157,0.005533409],"domain_codex":"methods","domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002318046,0.0001839747,0.7006094,0.007816749,0.003809263,0.0002314019,0.008883368,0.0055097,0.00123924,0.009332634,0.02126322,0.2388029],"study_design_scores_gemma":[0.0007862093,0.0007417531,0.8690209,0.01011837,0.002073823,0.000517045,0.003553132,0.008640393,0.005021766,0.006100107,0.09281142,0.0006151551],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4224457,0.1247715,0.07256236,0.2198684,0.003177728,0.01002649,0.03735369,0.0009875369,0.1088066],"genre_scores_gemma":[0.9462271,0.009837164,0.0245172,0.01086577,0.0008214485,0.001278567,0.004659198,0.0001923537,0.001601344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9356849,"threshold_uncertainty_score":0.9932227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4772771332571777,"score_gpt":0.4728201928599733,"score_spread":0.004456940397204345,"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."}}