{"id":"W4405697344","doi":"10.3390/app142411975","title":"Workload Assessment of Operators: Correlation Between NASA-TLX and Pupillary Responses","year":2024,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"China Scholarship Council","keywords":"Workload; Pupil diameter; Pupillary response; Pupillometry; Eye tracking; Task (project management); Psychology; Audiology; Pupil; Correlation; Pupil size; Ophthalmology; Medicine; Computer science; Artificial intelligence; Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000732755,0.0000746422,0.0001139389,0.0001868949,0.0001643706,0.000102285,0.00009114701,0.00005693949,0.001475275],"category_scores_gemma":[0.00001585832,0.00006039806,0.00002375587,0.0003666887,0.0002358569,0.000136723,0.00002950816,0.0001126719,0.0001232795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001930307,"about_ca_system_score_gemma":0.00006950264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001506307,"about_ca_topic_score_gemma":0.000004430986,"domain_scores_codex":[0.9990883,0.00007736059,0.0002470133,0.0002604314,0.0002092102,0.0001176258],"domain_scores_gemma":[0.9993405,0.000433805,0.00005581199,0.0001054531,0.00002277142,0.00004168718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00005677561,0.00009100275,0.1342073,0.00005846252,0.0001396732,0.000009026263,0.00895633,0.0001398068,0.005752521,0.7638136,0.009392217,0.07738337],"study_design_scores_gemma":[0.0003266884,0.0001834653,0.9620243,0.0001225486,0.00003325018,0.00001725007,0.004632964,0.002883734,0.0005970957,0.002592708,0.02634474,0.0002412012],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7714013,0.0002962835,0.002658867,0.0004314687,0.0007232944,0.0001529201,0.000009301084,0.0001010526,0.2242255],"genre_scores_gemma":[0.9978933,0.00001444904,0.0005867804,0.0000877392,0.00008305869,0.00002354349,0.000003396598,0.000004735913,0.001302993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8278171,"threshold_uncertainty_score":0.9994375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04805371780140312,"score_gpt":0.4206668368822363,"score_spread":0.3726131190808332,"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."}}