{"id":"W2152536341","doi":"10.1002/j.2055-2335.2011.tb00107.x","title":"Evidence on Optimal Prescribing and Medicines Use for Decision Makers: Scope and Application of the <i>Rx for Change</i> Database","year":2011,"lang":"en","type":"article","venue":"Journal of Pharmacy Practice and Research","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Population and Public Health; Canadian Agency for Drugs and Technologies in Health; University of Ottawa","funders":"Government of Canada","keywords":"Scope (computer science); Psychological intervention; Medicine; Database; Quality (philosophy); Resource (disambiguation); Health professionals; Health care; Nursing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.1175523,0.001211353,0.009004931,0.02365503,0.0006725377,0.01325855,0.005035265,0.004581817,0.03433301],"category_scores_gemma":[0.483784,0.001434677,0.005573555,0.02927315,0.001153111,0.004840262,0.006452799,0.003344431,0.003490677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004103991,"about_ca_system_score_gemma":0.01099714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004604748,"about_ca_topic_score_gemma":0.005094395,"domain_scores_codex":[0.8206286,0.06934655,0.08027428,0.004356478,0.02399264,0.001401448],"domain_scores_gemma":[0.3306538,0.53545,0.05509654,0.02823977,0.04681721,0.003742687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003500882,0.0001851337,0.007837827,0.1984486,0.006345611,0.0001475242,0.0009255647,0.002628705,0.000528847,0.01849937,0.3724985,0.3884533],"study_design_scores_gemma":[0.00668331,0.001073993,0.03019597,0.1819852,0.01337115,0.0003705283,0.000644662,0.003351175,0.002055678,0.01765724,0.7422177,0.0003932857],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.01396941,0.1332474,0.04366985,0.06988471,0.005298524,0.02820649,0.6055048,0.003125593,0.0970933],"genre_scores_gemma":[0.1253774,0.1228969,0.3117707,0.03094142,0.006439391,0.07661617,0.3130811,0.00210185,0.01077507],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1175523,"threshold_uncertainty_score":0.6216832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8594732559643884,"score_gpt":0.6165562105114732,"score_spread":0.2429170454529151,"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."}}