{"id":"W2020210343","doi":"10.2514/1.21900","title":"Effect of Simulator Motion on Pilot Behavior and Perception","year":2006,"lang":"en","type":"article","venue":"Journal of Aircraft","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Fidelity; Yaw; Flight simulator; Motion (physics); Simulation; Computer science; Task (project management); Driving simulator; Workload; Motion simulator; Motion capture; Engineering; Artificial intelligence; Automotive engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001146218,0.00005687532,0.0001259541,0.00009579946,0.00001288586,0.000004677196,0.00003204066,0.00005029574,0.00001701269],"category_scores_gemma":[0.00001202709,0.00004666643,0.00003498587,0.00004804065,0.00001582499,0.00007512103,0.000003888538,0.0001082957,0.000004733427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002953192,"about_ca_system_score_gemma":0.00000216966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003128875,"about_ca_topic_score_gemma":0.000001472002,"domain_scores_codex":[0.9996358,0.00001354592,0.0001706559,0.00003314915,0.00008952006,0.00005731222],"domain_scores_gemma":[0.9998094,0.00002960733,0.00006822004,0.00004749116,0.00002837299,0.00001686334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001573113,0.0002059803,0.131444,0.0001693687,0.0000375328,0.00002301121,0.00008719487,0.06254117,0.7357818,0.0001653912,0.002261671,0.06712558],"study_design_scores_gemma":[0.00252831,0.006814684,0.7775756,0.0001216268,0.0001500117,0.00008047314,0.00003839407,0.006889554,0.2050011,0.0001716685,0.0004333205,0.0001952744],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974324,0.00006393199,0.002201254,0.00005327634,0.0001067728,0.00005071934,0.000001096725,0.00003019335,0.00006035186],"genre_scores_gemma":[0.9997094,0.00002215953,0.0001472496,0.000004946022,0.00007952608,9.272925e-7,6.73331e-7,0.000008659091,0.0000264399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6461315,"threshold_uncertainty_score":0.1903002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003860950017728766,"score_gpt":0.2185075009111274,"score_spread":0.2146465508933986,"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."}}