{"id":"W4410436460","doi":"10.1007/s40520-025-03026-3","title":"Convergence and equating norms between the Telephone Interview for Cognitive Status (TICS), the MMSE and the MoCA in an Italian population sample","year":2025,"lang":"en","type":"article","venue":"Aging Clinical and Experimental Research","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministero della Salute","keywords":"Equating; Tics; Sample (material); Telephone interview; Convergence (economics); Population; Psychology; Cognitive impairment; Cognition; Demography; Telephone survey; Gerontology; Medicine; Psychiatry; Sociology; Developmental psychology; Economics; Advertising","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":[0.02051496,0.000559247,0.000510728,0.002632325,0.0006836092,0.001434017,0.001029309,0.0008628457,0.001464782],"category_scores_gemma":[0.07532388,0.0004402236,0.0005417063,0.001105595,0.001424658,0.001098195,0.001843268,0.0006509306,0.000725908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005900481,"about_ca_system_score_gemma":0.0006091137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005058529,"about_ca_topic_score_gemma":0.005453024,"domain_scores_codex":[0.9854963,0.007725129,0.001073208,0.002695834,0.002525826,0.000483637],"domain_scores_gemma":[0.9663097,0.01931555,0.003494853,0.004965656,0.005249542,0.0006646205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003849246,0.00009722195,0.9755912,0.00005090275,0.0002139569,0.0001940324,0.004203941,0.0004880598,0.0008391313,0.0005142271,0.0004446542,0.01697773],"study_design_scores_gemma":[0.00001973298,0.0003825512,0.9940938,0.00003078918,0.00006649525,0.0005871748,0.001113793,0.001807026,0.0003473383,0.0004938518,0.001033278,0.00002415053],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921865,0.0002580065,0.003873807,0.00006629283,0.00004257544,0.0001031482,0.0001823803,0.0000348075,0.003252373],"genre_scores_gemma":[0.9964606,0.00009029965,0.002229802,0.00003559681,0.0000418219,0.00009309546,0.0006034818,0.00003206071,0.0004133109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02051496,"threshold_uncertainty_score":0.1084948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8000424341366335,"score_gpt":0.6806966223514711,"score_spread":0.1193458117851623,"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."}}