{"id":"W4400879263","doi":"10.1080/00140139.2024.2379949","title":"Utilising raw psycho-physiological data and functional data analysis for estimating mental workload in human drivers","year":2024,"lang":"en","type":"article","venue":"Ergonomics","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Ministry of Science and ICT, South Korea; University of Windsor","keywords":"Workload; Raw data; Human factors and ergonomics; Raw score; Psychology; Poison control; Applied psychology; Computer science; Engineering; Medicine; Medical emergency","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":[0.0008050224,0.0006369022,0.0003651675,0.001497042,0.0001697102,0.0007593976,0.0002105927,0.0005557643,0.0006041293],"category_scores_gemma":[0.003590336,0.000173156,0.000356499,0.0005086166,0.0001938964,0.0006196018,0.0004182351,0.0002163909,0.000243954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001198038,"about_ca_system_score_gemma":0.0002695562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001050546,"about_ca_topic_score_gemma":0.002146869,"domain_scores_codex":[0.9995207,0.000167631,0.00004431603,0.00008577821,0.0001454964,0.00003608139],"domain_scores_gemma":[0.9988953,0.0005471823,0.0001333818,0.00006112731,0.0003201815,0.0000428218],"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":[0.001374762,0.0006244755,0.1137193,0.001308749,0.0004191429,0.000387127,0.001138443,0.01320362,0.2763937,0.0006426698,0.0009135461,0.5898745],"study_design_scores_gemma":[0.0001191031,0.003257037,0.6189622,0.0002661634,0.0004615909,0.001818513,0.002026823,0.2689251,0.09689776,0.002914932,0.00405407,0.0002966451],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8186738,0.0007385898,0.1775499,0.0001477523,0.00007860758,0.000215275,0.0005082955,0.000319984,0.001767691],"genre_scores_gemma":[0.9536538,0.0003298282,0.04531231,0.00005128958,0.00004464087,0.00007899072,0.0002157929,0.00001263216,0.0003007292],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001497042,"threshold_uncertainty_score":0.004257381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1799956057305184,"score_gpt":0.4399959011148218,"score_spread":0.2600002953843035,"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."}}