{"id":"W2596774957","doi":"","title":"Aircrew Pairings with Possible Repetitions of the Same Flight Number","year":2009,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Crew; Schedule; Computer science; Heuristic; Set (abstract data type); Phase (matter); Sequence (biology); Pairing; Aircrew; Mathematical optimization; Quality (philosophy); Mathematics; Engineering; Aeronautics; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0004425509,0.000261965,0.0002926272,0.0001464569,0.0001698229,0.00006902651,0.0004322907,0.0001836567,0.00007687581],"category_scores_gemma":[0.0001195206,0.0002075421,0.0001353701,0.0009455335,0.00008054428,0.0002292464,0.00005573441,0.0003812121,0.00001036629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002144081,"about_ca_system_score_gemma":0.00008867554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004446314,"about_ca_topic_score_gemma":0.000249446,"domain_scores_codex":[0.9984581,0.0001045023,0.0004138397,0.0002468261,0.0003152509,0.0004614555],"domain_scores_gemma":[0.9986393,0.00008077881,0.000130122,0.0008812827,0.0001243396,0.0001441507],"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":[0.00007585986,0.0003110031,0.1077031,0.0001416035,0.0001525132,0.00003158543,0.0009879284,0.7758362,0.03302897,0.05621428,0.007747762,0.01776919],"study_design_scores_gemma":[0.001175829,0.0002232437,0.2906427,0.0005230472,0.0001450467,0.0004277516,0.0001492341,0.5293981,0.1663289,0.004997359,0.004884007,0.001104866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1529899,0.0002825435,0.8299285,0.003990015,0.0001108363,0.0006175671,0.00002972593,0.0017076,0.01034341],"genre_scores_gemma":[0.7102037,0.0000507343,0.2881051,0.0007259985,0.00005389728,0.0000620668,0.000005406901,0.00005743812,0.0007357011],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5572138,"threshold_uncertainty_score":0.8463322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007451375031077562,"score_gpt":0.2238498106433354,"score_spread":0.2163984356122579,"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."}}