{"id":"W6901911920","doi":"10.6084/m9.figshare.11350370.v1","title":"MoCA Test: normative and diagnostic accuracy data for seniors with heterogeneous educational levels in Brazil","year":2019,"lang":"en","type":"dataset","venue":"Figshare","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Montreal Cognitive Assessment; Normative; Dementia; Cutoff; Cognition; Test (biology); Diagnostic accuracy; Epidemiology","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":[0.00288421,0.0006828965,0.001079362,0.004907385,0.0004575219,0.001069636,0.001709726,0.0007471621,0.01968992],"category_scores_gemma":[0.02828903,0.0003404719,0.001050216,0.005137588,0.0002913684,0.0006703116,0.00124468,0.0004691741,0.004033108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008891802,"about_ca_system_score_gemma":0.001642077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05941584,"about_ca_topic_score_gemma":0.06766026,"domain_scores_codex":[0.9982204,0.0004481783,0.0004275524,0.0004399711,0.0003456259,0.0001183037],"domain_scores_gemma":[0.9899796,0.003658464,0.001907608,0.001969036,0.002190833,0.000294458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001847325,0.0001697351,0.3450074,0.006622887,0.001116302,0.0004173706,0.0007726184,0.00228281,0.0007348065,0.002222948,0.5468778,0.09192794],"study_design_scores_gemma":[0.001037203,0.0001532048,0.7834496,0.003875629,0.000808864,0.001292477,0.0004868482,0.002801862,0.0005728115,0.002236582,0.2031393,0.0001454753],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02197027,0.0005054885,0.0004979647,0.0001925201,0.00003010205,0.000108174,0.9743733,0.000226025,0.002096074],"genre_scores_gemma":[0.08516689,0.0006958547,0.002764028,0.0001155951,0.00002459971,0.0009204557,0.9090735,0.0002016244,0.001037445],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05941584,"threshold_uncertainty_score":0.11814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09494372492367888,"score_gpt":0.3645270401163617,"score_spread":0.2695833151926828,"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."}}