{"id":"W2607329129","doi":"10.11159/icte17.120","title":"Air Traffic Flow Forecast in the Period of Major Events Based on Cost-Effectiveness Optimization","year":2017,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Civil, Structural, and Environmental Engineering","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Period (music); Air traffic control; Computer science; Flow (mathematics); Operations research; Engineering; Aerospace engineering; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003070006,0.0001966692,0.0002238961,0.0001264574,0.0001780908,0.000074841,0.001054208,0.00004677156,0.00000355091],"category_scores_gemma":[0.00003653539,0.000131502,0.00006809358,0.0001019581,0.00009195567,0.0003549087,0.000150761,0.0001659552,1.762491e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007761791,"about_ca_system_score_gemma":0.000004881166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005442337,"about_ca_topic_score_gemma":0.000004488624,"domain_scores_codex":[0.9990016,0.00001831775,0.0002204449,0.0002631026,0.0003166311,0.0001799024],"domain_scores_gemma":[0.9993181,0.00007776305,0.0002408708,0.0003199699,0.0000112222,0.0000320809],"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":[0.00009603894,0.00007363145,0.008154216,0.0004363002,0.00003573832,0.000002562564,0.0005752632,0.9689085,0.01283712,0.002500196,0.00003441014,0.006345951],"study_design_scores_gemma":[0.0005661286,0.0001082957,0.0476451,0.0005292354,0.000009853949,0.000009921763,0.00004198025,0.9145193,0.03628956,0.00009342828,0.00001657338,0.0001706574],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915298,0.00003506973,0.006040053,0.0002659142,0.0004312646,0.001288917,0.00001736726,0.00005969559,0.0003319845],"genre_scores_gemma":[0.9962205,0.000005087568,0.003630781,0.00002090242,0.0000155266,0.00007425702,0.000001246553,0.00001514775,0.00001650906],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05438931,"threshold_uncertainty_score":0.5362496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01009650579267535,"score_gpt":0.2202888134188099,"score_spread":0.2101923076261345,"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."}}