{"id":"W2769803457","doi":"10.1016/j.parkreldis.2017.11.337","title":"Associations between intra-individual variability and Montreal Cognitive Assessment (MoCA) in cognitive ageing and prodromal dementia: A domain-specific perspective","year":2017,"lang":"en","type":"letter","venue":"Parkinsonism & Related Disorders","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Montreal Cognitive Assessment; Dementia; Cognition; Perspective (graphical); Gerontology; Psychology; Ageing; Cognitive impairment; Disease; Medicine; Psychiatry; Computer science; Internal medicine; Artificial intelligence","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":[0.002918099,0.0002618451,0.00112543,0.0008517693,0.0006129284,0.00131567,0.000783213,0.005161004,0.001511084],"category_scores_gemma":[0.01908597,0.0002280757,0.0006565011,0.001267187,0.0007526826,0.001213491,0.0005540818,0.004200115,0.0004802029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008238181,"about_ca_system_score_gemma":0.0008437049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005088122,"about_ca_topic_score_gemma":0.009777998,"domain_scores_codex":[0.9981827,0.0005365739,0.0004273571,0.0002604641,0.0004289775,0.0001640907],"domain_scores_gemma":[0.9865865,0.00880366,0.00147325,0.0004454157,0.00218756,0.0005035978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001123952,0.0001550183,0.7438074,0.0004848956,0.000807936,0.01878252,0.0007564503,0.0005800375,0.001216752,0.003525987,0.1039,0.1248591],"study_design_scores_gemma":[0.0003019433,0.0005580787,0.8331126,0.0009025433,0.0008687223,0.04652605,0.002237533,0.004453378,0.0009367332,0.02737715,0.08251962,0.0002056478],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.214598,0.04909872,0.001992106,0.7040203,0.007489954,0.00004013142,0.0015455,0.0001122657,0.02110296],"genre_scores_gemma":[0.8578151,0.009531328,0.001664748,0.08663263,0.04063307,0.00005606685,0.0004071276,0.0000261426,0.003233725],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005161004,"threshold_uncertainty_score":0.01543254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01937671687995882,"score_gpt":0.315517177946305,"score_spread":0.2961404610663462,"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."}}