{"id":"W2073444771","doi":"10.1016/j.jval.2014.03.113","title":"Use Of Economic Evidence To Inform Drug Reimbursement Decision Making: The Case For Ontario","year":2014,"lang":"en","type":"article","venue":"Value in Health","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Formulary; Reimbursement; Logistic regression; Medicine; Evidence-based medicine; Actuarial science; Family medicine; Business; Alternative medicine; Economics; Economic growth; Health care","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.06565695,0.0005595533,0.001259842,0.005170237,0.003235878,0.01047924,0.002311633,0.004109313,0.003641503],"category_scores_gemma":[0.2529927,0.00065924,0.00123025,0.006794278,0.005747265,0.006035207,0.003488468,0.005902457,0.0001868353],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07321764,"about_ca_system_score_gemma":0.154236,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8979499,"about_ca_topic_score_gemma":0.9549288,"domain_scores_codex":[0.9612647,0.02017051,0.003115717,0.001214158,0.01162449,0.002610341],"domain_scores_gemma":[0.6273178,0.2593545,0.01706713,0.008979571,0.07949396,0.007786973],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001031369,0.0002361877,0.205641,0.004764346,0.002352198,0.001784694,0.006941284,0.01540756,0.0005788495,0.2270056,0.1605405,0.3737165],"study_design_scores_gemma":[0.0009415903,0.0002046935,0.1978772,0.02091258,0.002470346,0.0006625496,0.006691243,0.02514857,0.001274097,0.304331,0.4389286,0.0005574483],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06056392,0.03898935,0.006705177,0.7867506,0.0006646854,0.0002893951,0.002635178,0.00005618127,0.1033456],"genre_scores_gemma":[0.9157998,0.02792302,0.01794908,0.03226174,0.0007276314,0.0001407392,0.0008249486,0.00007368186,0.004299277],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.934343,"threshold_uncertainty_score":0.5312337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6180299669526403,"score_gpt":0.479337443169149,"score_spread":0.1386925237834913,"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."}}