{"id":"W3107559526","doi":"10.1155/2020/8835201","title":"A Tabu Search-Based Algorithm for Airport Gate Assignment: A Case Study in Kunming, China","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Air Traffic Management and Optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tabu search; International airport; Mathematical optimization; Computer science; Scheduling (production processes); Guided Local Search; Process (computing); Operations research; Engineering; Transport engineering; Algorithm; 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":[0.0001718547,0.0001116738,0.0001924651,0.0001321253,0.00003165864,0.00001470898,0.00006274506,0.00002848167,0.00001423192],"category_scores_gemma":[0.00000552712,0.0001125782,0.00006844319,0.0002300832,0.000007830559,0.0003229209,7.401813e-7,0.0001371426,4.406481e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004629563,"about_ca_system_score_gemma":0.00002247374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004938396,"about_ca_topic_score_gemma":0.00006092161,"domain_scores_codex":[0.9990945,0.00001334427,0.0004572637,0.0001008838,0.0001995635,0.0001343902],"domain_scores_gemma":[0.9996811,0.00001919642,0.0001175126,0.00004778009,0.00005907558,0.00007539173],"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":[0.00006385607,0.00009035923,0.0007960271,0.00007766223,0.00003464505,0.0008487907,0.004130983,0.9360156,0.00006460911,0.000004968268,0.00002100578,0.05785149],"study_design_scores_gemma":[0.004706528,0.0007088181,0.01344315,0.00005444205,0.00009384815,0.00001285944,0.004322848,0.9759806,0.0002363838,0.00001509896,0.0002584552,0.0001669711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.390755,0.00005360699,0.6085433,0.0000828152,0.00009483191,0.0004148904,0.000006687794,0.00003455531,0.00001434223],"genre_scores_gemma":[0.9456717,0.0000306075,0.05413036,0.00002853121,0.00006502278,0.00001742633,0.00002675038,0.0000243193,0.000005255677],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5549167,"threshold_uncertainty_score":0.4590808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0129899628407205,"score_gpt":0.246349548720185,"score_spread":0.2333595858794645,"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."}}