{"id":"W2003146599","doi":"10.1097/01.mlr.0000178217.84354.f1","title":"Booming Prescription Drug Expenditure","year":2005,"lang":"en","type":"article","venue":"Medical Care","topic":"Pharmaceutical Economics and Policy","field":"Economics, Econometrics and Finance","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Health Canada","keywords":"Per capita; Medical prescription; Cohort; Prescription drug; Population; Medicine; Population ageing; Demography; Gerontology; Environmental health","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":[0.0003624361,0.0001954101,0.0001673748,0.001814162,0.0005811664,0.001722564,0.0002742339,0.0004553875,0.005052914],"category_scores_gemma":[0.002258317,0.0001264021,0.0001960417,0.003888196,0.0004192003,0.0006129403,0.0005800527,0.0006795553,0.0004232512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01105782,"about_ca_system_score_gemma":0.007714919,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7681538,"about_ca_topic_score_gemma":0.8442276,"domain_scores_codex":[0.9993199,0.00004956039,0.00002953809,0.00005776331,0.000281979,0.000261313],"domain_scores_gemma":[0.9986503,0.0001203607,0.0003007138,0.00003604877,0.0006475793,0.0002450332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00013906,0.00006036129,0.8389702,0.0003544401,0.0001100198,0.0005169314,0.001257257,0.00207687,0.0009687621,0.009885869,0.03916487,0.1064954],"study_design_scores_gemma":[0.000004771333,0.00001413802,0.9594271,0.0001152682,0.00002645073,0.0001577951,0.0005942105,0.0006604728,0.0001840854,0.0003539596,0.03845391,0.000007875396],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8889052,0.01079224,0.0007674688,0.02020059,0.00009540934,0.00005991726,0.01823734,0.0001002342,0.06084164],"genre_scores_gemma":[0.9832313,0.006089545,0.0005059204,0.00117815,0.00006737693,0.00001243995,0.003901347,0.00000906951,0.005004902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7681538,"threshold_uncertainty_score":0.4664232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03361706033256837,"score_gpt":0.283547898356298,"score_spread":0.2499308380237296,"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."}}