{"id":"W2607065805","doi":"10.1017/s0266462317000149","title":"DRUG EVALUATION AND DECISION MAKING IN CATALONIA: DEVELOPMENT AND VALIDATION OF A METHODOLOGICAL FRAMEWORK BASED ON MULTI-CRITERIA DECISION ANALYSIS (MCDA) FOR ORPHAN DRUGS","year":2017,"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":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Multiple-criteria decision analysis; Orphan drug; Context (archaeology); Population; Medicine; Management science; Decision analysis; Reliability (semiconductor); Computer science; Risk analysis (engineering); Operations research; Engineering; Environmental health; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.1182221,0.001820197,0.002049211,0.007785191,0.00204142,0.008189842,0.00285116,0.002168866,0.00180786],"category_scores_gemma":[0.07957835,0.0006738745,0.0023543,0.004525518,0.00357819,0.001643858,0.005561854,0.001998194,0.000159834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02034263,"about_ca_system_score_gemma":0.03122625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01969875,"about_ca_topic_score_gemma":0.02273934,"domain_scores_codex":[0.8638898,0.1151913,0.007474068,0.003501749,0.008888122,0.001055095],"domain_scores_gemma":[0.8896768,0.07767748,0.006048506,0.003525344,0.02199567,0.001076273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001218149,0.00106214,0.01529528,0.02393195,0.001399145,0.0008115084,0.01171523,0.2620364,0.003232753,0.2182417,0.007701886,0.4533537],"study_design_scores_gemma":[0.00176393,0.002749908,0.03939768,0.03464344,0.001720621,0.0007573682,0.01846922,0.5841133,0.006588853,0.2069352,0.1021516,0.0007089011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2057227,0.02081358,0.7010906,0.009205142,0.0008205964,0.02168999,0.001435715,0.0002118716,0.03900985],"genre_scores_gemma":[0.3308561,0.002850091,0.6591372,0.0005479373,0.00007501274,0.005004475,0.0005292997,0.00002562347,0.0009742209],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1182221,"threshold_uncertainty_score":0.6252257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3411429897501823,"score_gpt":0.5784186831033785,"score_spread":0.2372756933531963,"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."}}