{"id":"W3183180288","doi":"10.1007/s40520-021-01943-7","title":"The Montreal Cognitive Assessment (MoCA): updated norms and psychometric insights into adaptive testing from healthy individuals in Northern Italy","year":2021,"lang":"en","type":"article","venue":"Aging Clinical and Experimental Research","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Università degli Studi di Milano-Bicocca; Università degli Studi di Milano","keywords":"Montreal Cognitive Assessment; Normative; Psychology; Discriminative model; Cognition; Item response theory; Computerized adaptive testing; Orientation (vector space); Psychometrics; Developmental psychology; Cognitive psychology; Cognitive impairment; Computer science; Psychiatry; Artificial intelligence; Mathematics; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002352189,0.0001983123,0.0004165471,0.0002985828,0.0006195793,0.0002242692,0.000134375,0.0001196287,0.00005521621],"category_scores_gemma":[0.001269037,0.0001350253,0.00006585558,0.001342586,0.0008587143,0.0001656672,0.0006133337,0.001188848,0.00002598808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001220659,"about_ca_system_score_gemma":0.0004705253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002324631,"about_ca_topic_score_gemma":0.001675807,"domain_scores_codex":[0.9958177,0.0009876559,0.0006324024,0.0007919596,0.00110334,0.0006669763],"domain_scores_gemma":[0.9941643,0.004490777,0.00007354374,0.0002183289,0.000555791,0.0004972963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006008753,0.0009958817,0.8767207,0.00001306558,0.0001692309,0.0002265739,0.0009010853,8.407918e-8,0.001352134,0.00004588295,0.00008763907,0.1188869],"study_design_scores_gemma":[0.005635458,0.00237014,0.9736782,0.0002396008,0.00002578159,0.00001324615,0.01245181,0.0006127705,0.003188039,0.001285227,0.0003449445,0.0001548233],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859129,0.007424374,0.00002662934,0.001650988,0.00006876331,0.0007083086,0.000008850978,0.00002197579,0.004177245],"genre_scores_gemma":[0.9972633,0.001188101,0.0004508578,0.0004707184,0.0001374265,0.0001347575,0.00009079473,0.00002355357,0.0002404752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1187321,"threshold_uncertainty_score":0.550617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1303571715713139,"score_gpt":0.4912563079268791,"score_spread":0.3608991363555651,"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."}}