{"id":"W4384157362","doi":"10.1016/j.ajp.2023.103691","title":"Optimal cut-off MoCA score for screening for mild cognitive impairment in elderly individuals in China: A systematic review and meta-analysis","year":2023,"lang":"en","type":"review","venue":"Asian Journal of Psychiatry","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Meta-analysis; Cochrane Library; PsycINFO; Montreal Cognitive Assessment; MEDLINE; Bivariate analysis; Medicine; Cognitive impairment; Systematic review; Internal medicine; Statistics; Disease; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005705234,0.0006456745,0.009757731,0.002576233,0.00008450566,0.00009048355,0.0003321145,0.000247418,0.00009837936],"category_scores_gemma":[0.0005695402,0.0004328431,0.00467016,0.001922271,0.00006733506,0.0001724485,0.00007940183,0.0008753493,0.000005200469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001045512,"about_ca_system_score_gemma":0.0008431717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005054767,"about_ca_topic_score_gemma":0.00007061277,"domain_scores_codex":[0.9940652,0.0006985505,0.003226659,0.0005590779,0.0007943553,0.0006561383],"domain_scores_gemma":[0.9964275,0.000482146,0.002073665,0.0002925098,0.0003902239,0.0003339954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.0001235334,0.0004149808,0.001076236,0.827911,0.1610539,0.0000745755,0.0001477269,6.588193e-7,5.518865e-9,0.00002167709,0.0006980065,0.008477749],"study_design_scores_gemma":[0.002604576,0.002366757,0.0009541858,0.2750994,0.7168672,0.0002713811,0.0008103354,0.0000082525,7.532296e-8,0.0001038565,0.0005940513,0.0003199528],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00008140431,0.9831142,0.001135527,0.002537678,0.00009169343,0.01260842,0.0003714151,0.00001021325,0.00004943247],"genre_scores_gemma":[0.0001435693,0.9906186,0.00574475,0.0003356773,0.0001397768,0.002358156,0.0001835157,0.0001044767,0.0003715123],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5558133,"threshold_uncertainty_score":0.9998124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1072507308749034,"score_gpt":0.4235016898298389,"score_spread":0.3162509589549354,"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."}}