{"id":"W2734890667","doi":"10.1016/j.vhri.2017.03.002","title":"Editorial comment on Health Technology Assessment (HTA): Good Practices & Principles. FIFARMA’s Position on HTA Processes in Latin America: The Devil Is in the Details","year":2017,"lang":"en","type":"editorial","venue":"Value in Health Regional Issues","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Australian Government","keywords":"Health technology; Latin Americans; Position (finance); Position paper; Political science; Engineering ethics; Medicine; Engineering; Business; Health care; Law; Pathology","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":[0.01367858,0.003118988,0.003919196,0.003484169,0.006068381,0.00890703,0.004260166,0.03186569,0.01653824],"category_scores_gemma":[0.06350701,0.001292901,0.003547135,0.002591763,0.004410061,0.005916381,0.002521337,0.0395072,0.01743372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005111502,"about_ca_system_score_gemma":0.009060216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006265676,"about_ca_topic_score_gemma":0.01323029,"domain_scores_codex":[0.9892631,0.001652167,0.001409751,0.001335606,0.005523649,0.000815642],"domain_scores_gemma":[0.9610581,0.01695308,0.002582386,0.00124417,0.01466121,0.003501009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007726252,0.000003229535,0.00001011067,0.00003645399,0.000003705082,0.00003533185,0.000009622981,0.000006684296,0.000008109013,0.0001902,0.9990038,0.0006850293],"study_design_scores_gemma":[0.00007210537,0.00001749489,0.0002491333,0.0006075308,0.00003836634,0.000161232,0.00008353138,0.0001196001,0.0001055534,0.002109187,0.9964056,0.00003069055],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00002786875,0.001319679,0.00008899665,0.1978854,0.7990356,0.00002051521,0.000147162,0.00004788521,0.001426967],"genre_scores_gemma":[0.0005446813,0.001901588,0.0001568586,0.1864097,0.8003447,0.00005824763,0.00007921586,0.00009327823,0.01041178],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.03186569,"threshold_uncertainty_score":0.07234013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4400999900830423,"score_gpt":0.5228224948741205,"score_spread":0.08272250479107818,"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."}}