{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004072729,0.0004739942,0.0003601644,0.0007672748,0.0001315596,0.0004060823,0.0003334383,0.0004348128,0.001123872],"category_scores_gemma":[0.002393215,0.0001463964,0.0002868259,0.0002208924,0.0001218195,0.0003097585,0.0003550874,0.0002748671,0.0003762801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001364781,"about_ca_system_score_gemma":0.0001533412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008590598,"about_ca_topic_score_gemma":0.001258041,"domain_scores_codex":[0.9996682,0.00006697835,0.0000250423,0.00009519688,0.0001072986,0.00003734247],"domain_scores_gemma":[0.9992828,0.0003033479,0.0001540273,0.00005454368,0.0001643794,0.00004096173],"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":[0.001881987,0.0003699583,0.06142171,0.0007541685,0.0001354563,0.0003517473,0.001062077,0.004550735,0.2894535,0.000428367,0.001863463,0.6377268],"study_design_scores_gemma":[0.00008758037,0.003490079,0.725563,0.0001863726,0.0001966235,0.002412851,0.0007673809,0.1070149,0.1540554,0.0007847697,0.005300096,0.0001410167],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8016003,0.001199573,0.1900335,0.0001764032,0.00008711607,0.0005267342,0.0008261931,0.001444134,0.004106042],"genre_scores_gemma":[0.9522397,0.0005160804,0.04541228,0.00006892006,0.00002995806,0.0002106728,0.0003589702,0.0000439562,0.001119383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001123872,"threshold_uncertainty_score":0.003759742,"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."}}