{"id":"W4312003699","doi":"10.1093/geroni/igac059.2477","title":"EXPLORING THE EFFICACY OF MOCA SCORE CORRECTIONS IN REDUCING THE INFLUENCE OF RACE/ETHNICITY","year":2022,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Montreal Cognitive Assessment; Ethnic group; Contingency table; Demography; Medicine; Race (biology); Gerontology; Cognition; Internal medicine; Psychology; Cognitive impairment; Psychiatry; Statistics; Mathematics; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03003988,0.0006741555,0.0006826993,0.001230732,0.0008357841,0.001096845,0.001203876,0.0005197132,0.001911431],"category_scores_gemma":[0.1262531,0.0002889484,0.0011999,0.001096239,0.0008273492,0.0009637649,0.0007844211,0.001101806,0.0004182682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004325874,"about_ca_system_score_gemma":0.001712098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009112776,"about_ca_topic_score_gemma":0.0133104,"domain_scores_codex":[0.9752157,0.01935866,0.001054722,0.002018786,0.001885397,0.000466657],"domain_scores_gemma":[0.9222267,0.05053944,0.0117762,0.008572179,0.0058637,0.001021803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005003734,0.0008305977,0.8172451,0.0002544515,0.00352736,0.0001547444,0.001513391,0.00389783,0.002896436,0.001682472,0.006972981,0.156021],"study_design_scores_gemma":[0.000214085,0.002817999,0.9645546,0.0001719898,0.001223794,0.000173064,0.0007911228,0.01685893,0.005091682,0.001239172,0.006794804,0.00006869053],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9678716,0.001108247,0.02131711,0.001457053,0.0003468941,0.0005816846,0.001152681,0.0003508393,0.005813892],"genre_scores_gemma":[0.98824,0.00008106518,0.009839281,0.0002202943,0.00006262774,0.0002745817,0.0003992745,0.00009259436,0.0007902606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03003988,"threshold_uncertainty_score":0.158868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09291470899222104,"score_gpt":0.3575365091223943,"score_spread":0.2646218001301733,"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."}}