{"id":"W4321505029","doi":"10.4236/jbbs.2023.132002","title":"Detection and Recuperation of Mental Fatigue","year":2023,"lang":"en","type":"article","venue":"Journal of Behavioral and Brain Science","topic":"Sleep and Work-Related Fatigue","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mental fatigue; Electroencephalography; Cognition; Mood; Psychology; Mental state; Relaxation (psychology); Physical medicine and rehabilitation; Computer science; Cognitive psychology; Artificial intelligence; Applied psychology; Clinical psychology; Psychiatry; Medicine; Neuroscience","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006993692,0.0000481332,0.00009041019,0.0002167897,0.0001215081,0.00002817878,0.00007465325,0.00004450528,0.00003171542],"category_scores_gemma":[0.00002203653,0.00003667842,0.000022848,0.000504432,0.0002621631,0.0002592268,0.00002377418,0.00011055,0.000002604858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001300582,"about_ca_system_score_gemma":0.00001898808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003852668,"about_ca_topic_score_gemma":0.00001244861,"domain_scores_codex":[0.9993383,0.00003126301,0.0002168224,0.0001003129,0.0002027711,0.0001105897],"domain_scores_gemma":[0.9996336,0.00003351764,0.0001341974,0.00005250642,0.00007726935,0.00006893389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00007317537,0.0000934659,0.04135691,0.000001864893,0.000008682738,0.00002250189,0.006859883,0.000005415917,0.3929265,0.0002525987,0.0005740726,0.557825],"study_design_scores_gemma":[0.002490893,0.002884235,0.9224477,0.0002603142,0.00008673509,0.0004505679,0.009536295,0.0002424995,0.06067365,0.000309936,0.0003273524,0.0002898115],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986441,0.0001044885,0.0000855354,0.0004035787,0.0005618653,0.00004782429,0.000001751488,0.000006831601,0.0001440227],"genre_scores_gemma":[0.9997309,0.00002611047,0.0001160629,0.00003259291,0.00003489354,8.881451e-7,3.568209e-7,0.000002603632,0.00005562012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8810908,"threshold_uncertainty_score":0.1495702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05929289831704254,"score_gpt":0.3744260764605703,"score_spread":0.3151331781435278,"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."}}