{"id":"W1970872931","doi":"10.1016/j.orhc.2013.03.001","title":"Multi-criteria decision analysis (MCDA) in health care: A bibliometric analysis","year":2013,"lang":"en","type":"article","venue":"Operations Research for Health Care","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":178,"is_retracted":false,"has_abstract":false,"ca_institutions":"Programs for Assessment of Technology in Health Research Institute; McMaster University","funders":"Pfizer Canada; Pfizer","keywords":"Multiple-criteria decision analysis; Health care; Decision analysis; Transparency (behavior); Management science; Operations research; Computer science; Medicine; Political science; Economics; Engineering; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.04367654,0.0009689591,0.00288932,0.06707371,0.00318603,0.007708755,0.001273452,0.001497288,0.003503244],"category_scores_gemma":[0.1821837,0.0005434797,0.002552431,0.09527066,0.002276791,0.006157122,0.003350433,0.001224788,0.0002757948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00763558,"about_ca_system_score_gemma":0.009633844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01242799,"about_ca_topic_score_gemma":0.01404933,"domain_scores_codex":[0.9372998,0.03760208,0.004866683,0.001202435,0.01843993,0.0005889296],"domain_scores_gemma":[0.8208432,0.1569629,0.005646788,0.003178188,0.01263782,0.000731184],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005159877,0.0007572945,0.06532871,0.01322513,0.00224383,0.0002800511,0.003567316,0.06496916,0.0007746303,0.1211444,0.008907063,0.7182864],"study_design_scores_gemma":[0.000298074,0.0008052608,0.1060266,0.006957513,0.003331936,0.00066437,0.01230213,0.5319725,0.002725982,0.3040586,0.03041251,0.0004444531],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4309497,0.06071762,0.4092799,0.01534502,0.0007368539,0.003508322,0.005512811,0.0004971189,0.07345265],"genre_scores_gemma":[0.8047949,0.01002603,0.1819674,0.0002374246,0.000284202,0.0009007993,0.0008409166,0.00003901729,0.0009093885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9563234,"threshold_uncertainty_score":0.2309864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3606274506282388,"score_gpt":0.6206862944118692,"score_spread":0.2600588437836304,"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."}}