{"id":"W4384695175","doi":"10.22215/etd/2023-15528","title":"Statistical Modeling of Air Traffic: Development of Methods and Application through a Canadian Case Study","year":2023,"lang":"en","type":"dissertation","venue":"","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Aviation; Kalman filter; Air traffic control; Operations research; Engineering; Aeronautics; National Airspace System; Trajectory; Computer science; Systems engineering; Transport engineering; Artificial intelligence; Aerospace 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004613337,0.0007470577,0.000437579,0.002304654,0.001672841,0.002014344,0.002135659,0.0008276953,0.00168719],"category_scores_gemma":[0.008366385,0.0004070089,0.0006907778,0.003693076,0.001202846,0.0009995264,0.001066759,0.001012013,0.0001557401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01630569,"about_ca_system_score_gemma":0.01438351,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8615193,"about_ca_topic_score_gemma":0.8462257,"domain_scores_codex":[0.9978976,0.000923193,0.00008056242,0.0002175596,0.000708689,0.0001723752],"domain_scores_gemma":[0.9963139,0.002320213,0.0001915623,0.0001694174,0.0009113652,0.00009355476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000078328,0.0002446739,0.02897965,0.0001967274,0.00007086847,0.0008892035,0.002472146,0.6469206,0.0009844439,0.2100541,0.004468536,0.1046407],"study_design_scores_gemma":[0.00002205867,0.00004346327,0.007002518,0.00008133632,0.00002780034,0.0001479064,0.00159973,0.9610369,0.0006782169,0.01294431,0.01636247,0.00005328223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2608618,0.001156393,0.6965601,0.002294468,0.00005773814,0.001018281,0.002282339,0.0003007106,0.03546824],"genre_scores_gemma":[0.5204231,0.001866816,0.4690019,0.00007424922,0.0000203368,0.0005880931,0.0009829695,0.00009926978,0.006943345],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1384807,"threshold_uncertainty_score":0.2785925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07391880458992062,"score_gpt":0.4017688503626579,"score_spread":0.3278500457727373,"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."}}