{"id":"W3047646135","doi":"10.1017/s0266462320000525","title":"Can multi-criteria decision analysis (MCDA) be implemented into real-world drug decision-making processes? A Canadian provincial experience","year":2020,"lang":"en","type":"article","venue":"International Journal of Technology Assessment in Health Care","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fraser Health; Centre for Advancing Health Outcomes; University of British Columbia","funders":"","keywords":"Multiple-criteria decision analysis; Decision analysis; Reimbursement; Context (archaeology); Management science; Computer science; Risk analysis (engineering); Process management; Operations research; Business; Political science; Economics; Engineering; 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":[],"consensus_categories":[],"category_scores_codex":[0.04754858,0.0007384708,0.0008335245,0.002495859,0.01690743,0.010438,0.004790902,0.002129954,0.005235157],"category_scores_gemma":[0.07209706,0.0008002265,0.001241295,0.006447241,0.006977671,0.002327105,0.004951504,0.004705908,0.0006137994],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.204649,"about_ca_system_score_gemma":0.3514508,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9835857,"about_ca_topic_score_gemma":0.9905229,"domain_scores_codex":[0.960126,0.02154773,0.001363483,0.00138188,0.01117379,0.004407219],"domain_scores_gemma":[0.9487722,0.02002812,0.001686327,0.002254232,0.02171946,0.00553967],"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":[0.001264209,0.001161762,0.05915431,0.006382807,0.0004190342,0.004569449,0.1235085,0.05800714,0.003093263,0.1992374,0.1039362,0.4392659],"study_design_scores_gemma":[0.0004421203,0.0005471659,0.05796231,0.005453865,0.0002355607,0.000717239,0.1049112,0.03327581,0.002423941,0.03028419,0.7632142,0.0005323915],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3306229,0.02741121,0.07509813,0.1911526,0.001792132,0.003773207,0.002382827,0.000585273,0.3671817],"genre_scores_gemma":[0.8800759,0.009137979,0.09150535,0.004708644,0.00008614269,0.0004091446,0.0005582273,0.0001679587,0.01335077],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.795351,"threshold_uncertainty_score":0.9224944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1455367097439479,"score_gpt":0.5109888375634045,"score_spread":0.3654521278194566,"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."}}