{"id":"W4388204217","doi":"10.1200/op.2023.19.11_suppl.149","title":"Who goes first? Patterns of cancer drug approvals across four major regulatory authorities: EMA, FDA, Health Canada, and PMDA.","year":2023,"lang":"en","type":"article","venue":"JCO Oncology Practice","topic":"Pharmaceutical Economics and Policy","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"National Institutes of Health","keywords":"Medicine; Drug approval; Marketing authorization; Authorization; Drug; Regulatory agency; Cancer drugs; Regulatory science; Orphan drug; Pharmacology; Agency (philosophy); Food and drug administration; Public administration; Political science; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00204064,0.0002013666,0.0007856809,0.0001332719,0.0002789534,0.00005118693,0.0002718384,0.0001599369,0.0002056612],"category_scores_gemma":[0.0004837279,0.0002412437,0.00007659194,0.0002230404,0.00012229,0.0003740692,0.0002162527,0.0003788384,0.00006717422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007032722,"about_ca_system_score_gemma":0.0007014974,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6240506,"about_ca_topic_score_gemma":0.6727708,"domain_scores_codex":[0.9977806,0.00009560921,0.0009174782,0.0005002409,0.00005551908,0.0006505189],"domain_scores_gemma":[0.9971658,0.001112563,0.001036709,0.0003460287,0.00005811353,0.000280763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003742606,0.0004145816,0.3437174,0.001589293,0.001111779,0.0001174443,0.01488976,0.000530821,0.00001426601,0.1795384,0.4293551,0.02834688],"study_design_scores_gemma":[0.0008984936,0.00008179828,0.1045123,0.00002935286,0.0000180693,0.00001540561,0.001289892,0.001410247,0.0000274852,0.002372476,0.8890904,0.0002540012],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8772963,0.003338861,0.00002680195,0.108942,0.001316366,0.0003910198,0.002373746,0.00004589222,0.006269066],"genre_scores_gemma":[0.9640457,0.01036141,0.0002873073,0.01771866,0.0004549133,0.0001333759,0.0000261835,0.00005773989,0.006914685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4597353,"threshold_uncertainty_score":0.9837633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07314741834660451,"score_gpt":0.37649837883215,"score_spread":0.3033509604855454,"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."}}