{"id":"W2912611128","doi":"10.1155/2019/8908935","title":"An Extended Boarding Strategy Accounting for the Luggage Quantity and Group Behavior","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Economic efficiency; Boarding school; Computer science; Transport engineering; Engineering; Simulation; Operations research; Microeconomics; Economics","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":[0.0004802679,0.00007398562,0.0002194222,0.0001025647,0.0001051095,0.00005825624,0.00008557092,0.00005181624,0.00007645916],"category_scores_gemma":[0.00001226335,0.00006343975,0.0001120582,0.0001181727,0.00001427022,0.0009420552,8.677579e-7,0.0001377653,0.000002313792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001935697,"about_ca_system_score_gemma":0.000007907539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001777792,"about_ca_topic_score_gemma":0.00005152527,"domain_scores_codex":[0.9991574,0.000006241233,0.000562484,0.0001296912,0.00004432676,0.00009984904],"domain_scores_gemma":[0.9989743,0.00005756137,0.0007644406,0.00009735979,0.00007113079,0.00003525458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001261139,0.0001591285,0.8675432,0.00004249575,0.0001304894,0.00000408209,0.0007257628,0.0301732,0.001779548,0.07464171,0.00001218347,0.02466211],"study_design_scores_gemma":[0.0007811502,0.00017111,0.9942987,0.0000112932,0.00006278912,0.000002378316,0.0009413151,0.001027161,0.00006506445,0.001931029,0.0006199381,0.00008808495],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9778563,0.0005603012,0.02104638,0.00007109219,0.0002423735,0.0001190964,0.00004363045,0.00000505713,0.00005580649],"genre_scores_gemma":[0.9977751,0.0001239605,0.001900742,0.00002790363,0.00009270465,0.000007595653,0.00002305574,0.00000976453,0.00003916416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1267555,"threshold_uncertainty_score":0.2586998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02850951002932837,"score_gpt":0.2744558337369784,"score_spread":0.24594632370765,"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."}}