{"id":"W1514984683","doi":"","title":"Validity of utilization review tools.","year":2000,"lang":"en","type":"letter","venue":"PubMed","topic":"Delphi Technique in Research","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Jewish General Hospital","funders":"","keywords":"Kappa; Table (database); Computer science; Sample (material); Medicine; External validity; Sample size determination; Data science; Statistics; Data mining; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.3195796,0.0005964598,0.001364742,0.02018126,0.001333432,0.004561344,0.002371518,0.001582625,0.00436463],"category_scores_gemma":[0.6252823,0.0004447372,0.002684192,0.01320061,0.003428835,0.006222592,0.00687266,0.001333983,0.0009319431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004045295,"about_ca_system_score_gemma":0.006205166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002916626,"about_ca_topic_score_gemma":0.004079343,"domain_scores_codex":[0.4809445,0.3517965,0.06383583,0.008099237,0.09126122,0.004062734],"domain_scores_gemma":[0.2396137,0.6007673,0.05860486,0.02938072,0.06934192,0.002291448],"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":[0.00160548,0.0004398543,0.7332875,0.005109426,0.001472599,0.0003466079,0.009505607,0.0009243613,0.000655472,0.008609352,0.008748349,0.2292954],"study_design_scores_gemma":[0.000334728,0.002379233,0.8554403,0.008682569,0.001734,0.00363287,0.01945722,0.01994975,0.004378742,0.02289544,0.06067704,0.000438199],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"commentary","genre_scores_codex":[0.7122008,0.0244421,0.06689739,0.01591039,0.002731914,0.009858353,0.01109192,0.0005315381,0.1563356],"genre_scores_gemma":[0.9722438,0.0009483319,0.02064741,0.001348925,0.000251006,0.002484234,0.001406428,0.0000565175,0.000613306],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.3195796,"threshold_uncertainty_score":0.8390795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4635672223336377,"score_gpt":0.4492385708049401,"score_spread":0.01432865152869767,"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."}}