{"id":"W2952113293","doi":"10.1109/thms.2019.2917194","title":"High Cognitive Load Assessment in Drivers Through Wireless Electroencephalography and the Validation of a Modified <i>N</i>-Back Task","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Human-Machine Systems","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Electroencephalography; Task (project management); Cognitive load; Cognition; n-back; Baseline (sea); Audiology; Elementary cognitive task; Computer science; Simulation; Physical medicine and rehabilitation; Psychology; Working memory; Medicine; Engineering; 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":[0.0005631984,0.0002526816,0.0004966565,0.0002733785,0.0001927192,0.00005546937,0.0001701008,0.0001349703,0.0009079176],"category_scores_gemma":[0.000003658196,0.0001990233,0.0001710953,0.000372884,0.0002104934,0.00024996,0.00000191456,0.0005498356,0.0001233207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001282448,"about_ca_system_score_gemma":0.0000462551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004641399,"about_ca_topic_score_gemma":0.0003876293,"domain_scores_codex":[0.9974096,0.000791323,0.0007262627,0.0004281828,0.000385707,0.0002589502],"domain_scores_gemma":[0.9985133,0.0005082455,0.0003644634,0.0003531453,0.0002138426,0.00004694781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"randomized_trial","study_design_scores_codex":[0.0122015,0.01043689,0.01411629,0.001874684,0.007637288,0.00006220676,0.1788912,0.1511804,0.03641854,0.565892,0.00281349,0.01847553],"study_design_scores_gemma":[0.3424751,0.01507687,0.1724174,0.0084897,0.003802514,0.00082395,0.1663371,0.2183186,0.04396237,0.01191321,0.006408421,0.009974885],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8571876,0.00006690323,0.1210233,0.0002136377,0.002107084,0.001770767,0.0001435343,0.0000874601,0.01739969],"genre_scores_gemma":[0.9983419,0.00003807383,0.00001935811,0.0001377409,0.0000357081,0.0002591621,0.0000312869,0.00002640504,0.001110341],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5539788,"threshold_uncertainty_score":0.9941061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02192670853387144,"score_gpt":0.3355259066879152,"score_spread":0.3135991981540437,"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."}}