{"id":"W1975879435","doi":"10.1097/01.mlr.0000129494.36245.4b","title":"Drug Spending in Canada","year":2004,"lang":"en","type":"article","venue":"Medical Care","topic":"Pharmaceutical Economics and Policy","field":"Economics, Econometrics and Finance","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; U.S. Food and Drug Administration","keywords":"Per capita; Medical prescription; Inflation (cosmology); Drug prices; Public economics; Drug; Investment (military); Economics; Prescription drug; Demographic economics; Medicine; Environmental health; Pharmacology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004692106,0.0003036446,0.0002347376,0.003702563,0.002148569,0.002138076,0.0006509455,0.0004212047,0.008880357],"category_scores_gemma":[0.003001876,0.0001638781,0.0004391822,0.007541271,0.0004842729,0.0003886581,0.0006550302,0.000717177,0.0005166863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07370242,"about_ca_system_score_gemma":0.104298,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9958661,"about_ca_topic_score_gemma":0.9962184,"domain_scores_codex":[0.9986832,0.00006392356,0.00004739983,0.00008593059,0.000675939,0.0004435838],"domain_scores_gemma":[0.9968169,0.0001596598,0.000362136,0.00004091544,0.001879415,0.0007409048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000283447,0.0001039118,0.5946963,0.001089322,0.0003171146,0.0005849816,0.001123671,0.004184686,0.0005518838,0.01758704,0.2642748,0.1152029],"study_design_scores_gemma":[0.00002678721,0.0000276824,0.8804433,0.0002112234,0.00008336719,0.0001760632,0.0005634417,0.001476133,0.0002082413,0.0004479907,0.1163073,0.00002838615],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5266482,0.02592135,0.0006465813,0.04460977,0.0005275698,0.0002532747,0.2022981,0.000404709,0.1986905],"genre_scores_gemma":[0.9258035,0.01511874,0.0007174815,0.002064071,0.0001433747,0.00007305911,0.03354111,0.00004413171,0.02249456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07370242,"threshold_uncertainty_score":0.5347511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03267895508712495,"score_gpt":0.2637878098878245,"score_spread":0.2311088548006995,"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."}}