{"id":"W2911540048","doi":"10.3899/jrheum.181218","title":"Instrument Selection Using the OMERACT Filter 2.1: The OMERACT Methodology","year":2019,"lang":"en","type":"article","venue":"The Journal of Rheumatology","topic":"Delphi Technique in Research","field":"Social Sciences","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Work & Health; University of Ottawa","funders":"Leeds Biomedical Research Centre; School of Medicine, University of Alabama at Birmingham; Eli Lilly Australia; Vrije Universiteit Amsterdam; Sorbonne Université; Institut National de la Santé et de la Recherche Médicale; Agence Nationale de la Recherche; Pfizer Australia; Amsterdam University Medical Centers; National Institute for Health and Care Research; University of Leeds; Laboratoire d'Excellence Inflamex; Sydney Medical School; Ottawa Hospital Research Institute; Pfizer; Johns Hopkins University; Eli Lilly and Company; University of Ottawa; U.S. Department of Veterans Affairs","keywords":"Construct validity; Filter (signal processing); Set (abstract data type); Population; Computer science; Selection (genetic algorithm); Medical physics; Psychology; Artificial intelligence; Medicine; Psychometrics; Clinical psychology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01308171,0.0001065379,0.0003009258,0.0001368901,0.0006955498,0.00005871058,0.001185662,0.00013332,0.0007218317],"category_scores_gemma":[0.001175572,0.0000473194,0.0001258404,0.0004437101,0.0006056285,0.0001951107,0.0001368415,0.0009362933,0.00006149487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001660653,"about_ca_system_score_gemma":0.000394067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005288535,"about_ca_topic_score_gemma":0.0006079527,"domain_scores_codex":[0.9926897,0.005741269,0.0004844741,0.00009822113,0.0005646079,0.0004216874],"domain_scores_gemma":[0.9934304,0.005337304,0.0006150819,0.0002840062,0.0002782537,0.00005495475],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00227157,0.0004432577,0.5809419,0.00009877329,0.001727022,0.00002925416,0.1229698,0.003804887,0.04418783,0.08616647,0.06211858,0.0952407],"study_design_scores_gemma":[0.003192723,0.002311021,0.02527056,0.0005128384,0.0005932385,0.03296614,0.1379565,0.01019559,0.01441521,0.1133508,0.6580339,0.001201502],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9634331,0.0002255411,0.00344705,0.02999828,0.001018195,0.0003435806,5.435336e-7,0.00001662422,0.001517095],"genre_scores_gemma":[0.9965256,0.0008842064,0.001798534,0.0004243997,0.00005218707,0.000003415862,1.203305e-7,0.00001273237,0.0002988018],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5959153,"threshold_uncertainty_score":0.7994718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2319471776990591,"score_gpt":0.4701745187867887,"score_spread":0.2382273410877296,"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."}}