{"id":"W2942830767","doi":"10.1155/2019/1208279","title":"A New Air Traffic Flow Management User-Driven Prioritisation Process for Low Volume Operator in Constraint: Simulations and Results","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Air Traffic Management and Optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Flexibility (engineering); Air traffic control; Computer science; Aviation; Operations research; Process (computing); Constraint (computer-aided design); Traffic volume; Transport engineering; Simulation; 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":[0.0000941741,0.0001074068,0.0001650199,0.0001904822,0.0000267023,0.00001809221,0.00005543613,0.00004795821,0.00001322877],"category_scores_gemma":[0.000007501184,0.0001162669,0.00003823198,0.0001838243,0.000008095179,0.0006146195,7.47798e-7,0.00008202603,0.000001015661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004777218,"about_ca_system_score_gemma":0.00002155033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.417151e-7,"about_ca_topic_score_gemma":0.00006275747,"domain_scores_codex":[0.9990662,0.000006501682,0.0005476476,0.0001172882,0.0001444193,0.0001179706],"domain_scores_gemma":[0.999643,0.00002523327,0.0001339578,0.00005760731,0.0000904721,0.00004975731],"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":[0.0001364671,0.00001965508,0.000476881,0.0002557966,0.0000275766,0.000003603258,0.001412821,0.9717684,0.00009561751,0.0001163708,0.00003859171,0.02564826],"study_design_scores_gemma":[0.007007961,0.0001819149,0.05837855,0.0003690987,0.00007043302,0.000001655189,0.0009905456,0.9313732,0.0001068635,0.0001131495,0.001194536,0.0002120933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8333464,0.00005671568,0.1653289,0.0001178328,0.0002609038,0.0007484545,0.00002896633,0.00004305438,0.0000688594],"genre_scores_gemma":[0.9495475,0.00009946076,0.05006137,0.00001275966,0.0000463774,0.000006937423,0.0001181075,0.0000186518,0.00008888292],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1162011,"threshold_uncertainty_score":0.4741228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004850744123562089,"score_gpt":0.2213765646356595,"score_spread":0.2165258205120974,"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."}}