{"id":"W4388040963","doi":"10.3390/aerospace10110933","title":"Assessing Flight Crew Fatigue under Extra Augmented Crew Schedule Using a Multimodality Approach","year":2023,"lang":"en","type":"article","venue":"Aerospace","topic":"Sleep and Work-Related Fatigue","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Crew; Psychomotor vigilance task; Aeronautics; Vigilance (psychology); Aviation; Civil aviation; Psychomotor learning; Aircrew; Duty; Crew scheduling; Aviation accident; Mental fatigue; Booster (rocketry); Computer science; Medicine; Psychology; Sleep deprivation; Applied psychology; Engineering; Cognition","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004999788,0.0004932045,0.0002852156,0.0005479771,0.0001357289,0.0003031251,0.0002022713,0.0003655131,0.0007656504],"category_scores_gemma":[0.001283964,0.0001367511,0.000376871,0.0001884755,0.000129574,0.0002267029,0.0003198851,0.0001702807,0.00009818083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001914256,"about_ca_system_score_gemma":0.0001975508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002837767,"about_ca_topic_score_gemma":0.003368376,"domain_scores_codex":[0.9998003,0.00007769228,0.00001282285,0.00005704496,0.00003580509,0.00001642633],"domain_scores_gemma":[0.9996473,0.0001435382,0.00008911605,0.00003018694,0.00006218741,0.00002762127],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002658492,0.001283398,0.39043,0.0006245675,0.0005192488,0.0006174812,0.002404282,0.1359264,0.1884599,0.0005831244,0.0006628,0.2758304],"study_design_scores_gemma":[0.00006389265,0.005561356,0.584049,0.0000541324,0.0001749001,0.0004658294,0.0007879226,0.3978818,0.009325531,0.0007028343,0.0008388209,0.0000939137],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9656771,0.0001139372,0.03350078,0.00002829594,0.000005879032,0.00007054594,0.0001188154,0.0000419122,0.000442861],"genre_scores_gemma":[0.9938208,0.00005286655,0.005775973,0.000013352,0.000006108109,0.00006623266,0.00008873684,0.000002620997,0.0001731982],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002837767,"threshold_uncertainty_score":0.005642533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1917560620554771,"score_gpt":0.4147339599057134,"score_spread":0.2229778978502363,"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."}}