{"id":"W7029449871","doi":"","title":"Investigating the measurement precision of the montreal cognitive assessment (MoCA) for cognitive screening in parkinson’s disease through item response theory","year":2025,"lang":"en","type":"other","venue":"Lume (Universidade Federal do Rio Grande do Sul)","topic":"Biomedical and Chemical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação de Apoio à Pesquisa do Distrito Federal; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Item response theory; Differential item functioning; Montreal Cognitive Assessment; Cognition; Psychometrics; Recall; Portuguese; European Portuguese","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":[0.04762056,0.001321621,0.001019313,0.003650271,0.0007297808,0.001786229,0.001445393,0.001150793,0.001082988],"category_scores_gemma":[0.1259074,0.0005085357,0.003053799,0.002890797,0.00141743,0.00117711,0.001662436,0.001044012,0.0002193565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001576438,"about_ca_system_score_gemma":0.002360192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01215004,"about_ca_topic_score_gemma":0.01377966,"domain_scores_codex":[0.9783628,0.01558903,0.001271822,0.002057559,0.002308074,0.0004105855],"domain_scores_gemma":[0.9304836,0.05094843,0.008129113,0.005288969,0.00456213,0.0005876101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002040058,0.0001616875,0.9535035,0.0002303708,0.001465756,0.00005330317,0.001479488,0.003257644,0.0003059935,0.001298547,0.0004877537,0.03755195],"study_design_scores_gemma":[0.00008477985,0.0008091213,0.9565551,0.0004441084,0.0006069402,0.0003414843,0.001282635,0.03258518,0.0005287555,0.004942739,0.001745537,0.00007362121],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.951833,0.0024938,0.03974924,0.0006537127,0.0001193832,0.0005393646,0.0009452614,0.00009690097,0.003569341],"genre_scores_gemma":[0.988134,0.0002652106,0.01057538,0.00007231251,0.00002073923,0.0003107233,0.0005134738,0.00001538024,0.00009283383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04762056,"threshold_uncertainty_score":0.2518446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03560936569436807,"score_gpt":0.3129319102366066,"score_spread":0.2773225445422385,"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."}}