{"id":"W4206324549","doi":"10.3390/s22020535","title":"Simultaneous Classification of Both Mental Workload and Stress Level Suitable for an Online Passive Brain–Computer Interface","year":2022,"lang":"en","type":"article","venue":"Sensors","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Workload; Brain–computer interface; Computer science; Stress (linguistics); Interface (matter); Transfer of learning; Cognition; Electroencephalography; Artificial intelligence; Psychology; Psychiatry","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":[0.0001108728,0.0001485496,0.0001855882,0.00008414991,0.0002228614,0.00005136089,0.0002817092,0.00003860917,0.00002566739],"category_scores_gemma":[0.0001026361,0.0001425154,0.00004644236,0.0001357979,0.0001062503,0.0001141623,0.0001977815,0.0001643639,0.000001292172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004855675,"about_ca_system_score_gemma":0.00002252557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003291617,"about_ca_topic_score_gemma":0.00004898797,"domain_scores_codex":[0.9986409,0.0001737969,0.0002515104,0.0004664789,0.0002183661,0.0002489702],"domain_scores_gemma":[0.9986882,0.0008239326,0.0001596841,0.0002204331,0.00003660058,0.00007116955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004432147,0.001017782,0.0006192464,0.00009919941,0.00003551019,0.00002166791,0.009571785,0.07325912,0.8226091,0.0004894722,0.003649851,0.08818406],"study_design_scores_gemma":[0.001053341,0.001528451,0.001353628,0.0000565549,0.00001457178,0.00007015318,0.003028723,0.7392904,0.2453779,0.0001443263,0.007745706,0.0003362671],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948002,0.00003733529,0.002105606,0.000893765,0.0004077554,0.0003955945,0.001258242,0.00005460904,0.00004696913],"genre_scores_gemma":[0.9965439,0.000006768403,0.001783165,0.0004073078,0.00008814355,0.00001356202,0.00003115248,0.00002169018,0.001104238],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6660313,"threshold_uncertainty_score":0.5811608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06946407488833116,"score_gpt":0.3115431671511458,"score_spread":0.2420790922628147,"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."}}