{"id":"W2726844570","doi":"10.1093/geroni/igx004.4843","title":"WHAT POLICIES ARE IN USE ACROSS CANADA TO REDUCE INAPPROPRIATE MEDICATION USE IN OLDER ADULTS?","year":2017,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Agency for Drugs and Technologies in Health; Women's College Hospital; Alberta Health Services; University of Calgary; Université de Montréal; University of Alberta","funders":"","keywords":"Listing (finance); Medicine; Incentive; Medical prescription; Pharmaceutical Benefits Scheme; Family medicine; Authorization; Health care; Business; Nursing; Political science; Finance","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":[],"consensus_categories":[],"category_scores_codex":[0.01389366,0.0002675655,0.0006034784,0.003101566,0.009901775,0.00717938,0.002456222,0.001969194,0.001736237],"category_scores_gemma":[0.0542708,0.0003862028,0.0005074614,0.006733113,0.004266036,0.002685282,0.001894335,0.001652355,0.0001277815],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1454749,"about_ca_system_score_gemma":0.4078208,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9871448,"about_ca_topic_score_gemma":0.9937252,"domain_scores_codex":[0.9837314,0.002599144,0.001073861,0.0007203899,0.007844597,0.004030554],"domain_scores_gemma":[0.9185483,0.01030892,0.0117363,0.001402316,0.04068767,0.01731639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000251931,0.0003988928,0.5478997,0.002881894,0.0002803927,0.0007986751,0.03927649,0.001627821,0.001670522,0.02124321,0.05788745,0.3257829],"study_design_scores_gemma":[0.0000904,0.0001548813,0.8140639,0.00301131,0.0002273701,0.0002020265,0.0557925,0.001056743,0.001039985,0.002261276,0.1219403,0.0001592835],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5798024,0.02592447,0.001787705,0.3162149,0.0005090896,0.0006185708,0.00214245,0.0002282511,0.07277217],"genre_scores_gemma":[0.9649199,0.01027256,0.004987696,0.0170943,0.00008171239,0.0001321258,0.0003279311,0.00002082717,0.002163005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1454749,"threshold_uncertainty_score":0.991128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1439294624936193,"score_gpt":0.4357475484787371,"score_spread":0.2918180859851177,"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."}}