{"id":"W2792976615","doi":"10.1177/0361198118782272","title":"Exploration of the Evolution of Airport Ground Delay Programs","year":2018,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Air Traffic Management and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Geology; Business; Transport engineering; Engineering","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":[0.00287422,0.0001815416,0.0003211076,0.0006590722,0.0003249959,0.00004557298,0.0009009273,0.0001502078,0.0001211818],"category_scores_gemma":[0.00007506748,0.0001251663,0.0003078704,0.002631017,0.0008425548,0.0009554503,0.000007660775,0.0008695574,0.000006096427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002551772,"about_ca_system_score_gemma":0.0002887764,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002124238,"about_ca_topic_score_gemma":0.01965134,"domain_scores_codex":[0.9947643,0.0004683268,0.001352277,0.000207946,0.00272935,0.000477852],"domain_scores_gemma":[0.9952731,0.0001928905,0.0004533305,0.0004594543,0.00349714,0.0001241356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003269049,0.001353269,0.5682274,0.003173011,0.001213116,0.00003772732,0.02321183,0.2564343,0.0171981,0.04104474,0.02055052,0.06428694],"study_design_scores_gemma":[0.00178817,0.001194539,0.9590791,0.0008552073,0.0001478654,5.074516e-7,0.005528296,0.01229183,0.006687628,0.00543881,0.006713409,0.0002745859],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9573275,0.0001610891,0.03934962,0.0005887548,0.0007406181,0.001137524,0.0000182013,0.00003901213,0.000637645],"genre_scores_gemma":[0.9971638,0.0004298881,0.001755643,0.000004865351,0.0001743086,0.00004125451,0.00001548134,0.00004251603,0.0003722346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3908517,"threshold_uncertainty_score":0.9982375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0755345357278912,"score_gpt":0.3308728079057279,"score_spread":0.2553382721778367,"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."}}