{"id":"W2096169562","doi":"10.1186/1472-6963-11-329","title":"Bridging health technology assessment (HTA) with multicriteria decision analyses (MCDA): field testing of the EVIDEM framework for coverage decisions by a public payer in Canada","year":2011,"lang":"en","type":"article","venue":"BMC Health Services Research","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":136,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Rehabilitation Institute; Workplace Safety & Insurance Board; Centre Hospitalier Universitaire Sainte-Justine; Inro Consultants (Canada)","funders":"Workplace Safety and Insurance Board","keywords":"Multiple-criteria decision analysis; Decision analysis; Health technology; Context (archaeology); Management science; Medicine; Health informatics; Health care; Operations research; Public health; Nursing; Statistics; Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.4545206,0.001446641,0.002823218,0.009201333,0.008861759,0.0110621,0.006844688,0.004388263,0.00238723],"category_scores_gemma":[0.6111327,0.001549191,0.002587446,0.01064782,0.01007114,0.005772581,0.01246793,0.006217101,0.0001933136],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.1710825,"about_ca_system_score_gemma":0.323579,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.710541,"about_ca_topic_score_gemma":0.7828007,"domain_scores_codex":[0.6045345,0.3035239,0.02175349,0.007662559,0.05518138,0.007344043],"domain_scores_gemma":[0.2915276,0.5876781,0.01321195,0.01408934,0.08931585,0.004177161],"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":[0.003578656,0.003343586,0.03376383,0.02915769,0.001757334,0.0011264,0.08708846,0.05403866,0.00132153,0.1134973,0.01235163,0.6589751],"study_design_scores_gemma":[0.01029594,0.01290542,0.1290221,0.0845675,0.00400847,0.0006353537,0.09208386,0.3000139,0.00744825,0.2130035,0.1439667,0.002049111],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5426563,0.02967767,0.1864821,0.06705814,0.000854692,0.09039628,0.002101515,0.0003319551,0.0804414],"genre_scores_gemma":[0.7454527,0.003001535,0.2357882,0.001921629,0.0000731867,0.01270929,0.0003190208,0.00003271717,0.0007016995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8289175,"threshold_uncertainty_score":0.9614269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6329459906396536,"score_gpt":0.567753987714513,"score_spread":0.0651920029251406,"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."}}