{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006531279,0.0003918209,0.0004223214,0.0002015353,0.0004395643,0.0002368847,0.0003491578,0.0004869397,0.0005981018],"category_scores_gemma":[0.00006853497,0.0003839444,0.0001828259,0.001463431,0.0001687611,0.0004028856,0.0001399237,0.0006289975,0.0007693933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001658968,"about_ca_system_score_gemma":0.00007625325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007252605,"about_ca_topic_score_gemma":0.00002606319,"domain_scores_codex":[0.9970382,0.0003597702,0.00044248,0.0008515242,0.0003940613,0.0009140064],"domain_scores_gemma":[0.998387,0.0002241258,0.0002078276,0.0008514311,0.00009502408,0.0002346372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001008661,0.009672961,0.2771447,0.000477868,0.009587886,0.0009659233,0.05081178,0.09521712,0.1131258,0.1733464,0.1554576,0.1131832],"study_design_scores_gemma":[0.03693537,0.0007222166,0.6217144,0.004076596,0.00266449,0.0002836248,0.09359542,0.1982435,0.02152844,0.002454622,0.006804822,0.01097647],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8708367,0.0007341559,0.07951132,0.0008452614,0.001442596,0.0005914775,0.00001375842,0.001054079,0.04497065],"genre_scores_gemma":[0.9855087,0.00001261697,0.01203236,0.0003244232,0.0001886116,0.00006320464,0.0001023014,0.0001008721,0.001666922],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3445697,"threshold_uncertainty_score":0.9998612,"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."}}