{"id":"W4404512310","doi":"10.1016/j.ynirp.2024.100228","title":"Measuring cognitive load in multitasking using mobile fNIRS","year":2024,"lang":"en","type":"article","venue":"Neuroimage Reports","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Human multitasking; Cognitive load; Computer science; Cognition; Cognitive psychology; Psychology; Human–computer interaction; 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":[0.0003784439,0.0001977335,0.0002009735,0.0002020459,0.00009167595,0.0003055035,0.0001178536,0.00005113431,0.00003587668],"category_scores_gemma":[0.0007373847,0.0001890253,0.00009337295,0.0004457881,0.00008507194,0.0004704167,0.0001584287,0.0003684548,0.00003212766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001046105,"about_ca_system_score_gemma":0.0001285211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007235764,"about_ca_topic_score_gemma":0.00001161142,"domain_scores_codex":[0.9977288,0.0001208465,0.0004331323,0.0008972184,0.0004463923,0.0003736567],"domain_scores_gemma":[0.9991348,0.0004006781,0.00009591788,0.0002492326,0.00004671808,0.00007263751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001157822,0.00008354503,0.002351742,0.0001169079,0.000005539292,0.04327733,0.001133471,0.001143535,0.9303343,0.0000116216,0.00008544495,0.02144499],"study_design_scores_gemma":[0.0002091772,0.00008678752,0.001881079,0.001073786,0.00002234755,0.006737319,0.000119121,0.06332279,0.9230469,0.0002064944,0.002865362,0.0004288431],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918526,0.0003797477,0.0008027951,0.00002889712,0.001489796,0.0003315038,0.000004591951,0.0002765301,0.004833493],"genre_scores_gemma":[0.9991858,0.00001649043,0.0002090485,0.0002053838,0.0001184839,0.00001905173,6.194392e-7,0.00004169549,0.0002034239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06217926,"threshold_uncertainty_score":0.7708228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08234106065894754,"score_gpt":0.3219782753165832,"score_spread":0.2396372146576357,"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."}}