{"id":"W3204823703","doi":"10.1109/tnsre.2021.3118918","title":"A Machine-Learning-Based Assessment Method for Early-Stage Neurocognitive Impairment by an Immersive Virtual Supermarket","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Neurocognitive; Cognition; Cognitive flexibility; Executive functions; Psychology; Flexibility (engineering); Working memory; Montreal Cognitive Assessment; Set (abstract data type); Cognitive psychology; Computer science; Cognitive impairment; Psychiatry","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":[0.000921499,0.0006023556,0.0005049952,0.001271248,0.000184991,0.0004477621,0.0005247379,0.0004665749,0.001371145],"category_scores_gemma":[0.002535346,0.0001572008,0.0005197922,0.0006396918,0.000166304,0.00061823,0.0004862162,0.0003121858,0.0002466892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00026758,"about_ca_system_score_gemma":0.0003086522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001705553,"about_ca_topic_score_gemma":0.001732387,"domain_scores_codex":[0.9993705,0.0001818676,0.00004914738,0.0001476047,0.0002044221,0.00004641037],"domain_scores_gemma":[0.9993508,0.0002692748,0.00008534084,0.00004274396,0.0002197642,0.00003203879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001137842,0.000847138,0.03532155,0.0002629695,0.0002968164,0.0002849524,0.0002790242,0.05168081,0.04138119,0.001408437,0.002223589,0.8648757],"study_design_scores_gemma":[0.00007885308,0.001143432,0.05430858,0.00004398489,0.0001926191,0.000580752,0.0001505153,0.9239563,0.01581541,0.001106462,0.002523716,0.00009946162],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.29349,0.0004171659,0.7001867,0.000146452,0.00009895621,0.0004717836,0.000546281,0.001202202,0.003440428],"genre_scores_gemma":[0.8246921,0.0002063678,0.1729344,0.00006476403,0.00002947355,0.0004134284,0.0004048202,0.00002456633,0.001230073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001705553,"threshold_uncertainty_score":0.004873455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009858468570746211,"score_gpt":0.3007307669047035,"score_spread":0.2908722983339573,"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."}}