{"id":"W2052839955","doi":"10.1061/(asce)0733-947x(2004)130:3(274)","title":"Sizing the Baggage Claim Area for the New Large Aircraft","year":2004,"lang":"en","type":"article","venue":"Journal of Transportation Engineering","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Arup Group (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Sizing; Deck; Computer science; Cluster (spacecraft); Cockpit; Aviation; Automotive engineering; Transport engineering; Aerospace engineering; Engineering; Structural engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001721755,0.0001085091,0.0001146195,0.00005520686,0.00008270513,0.00002573631,0.0001385651,0.00004108573,0.000006352854],"category_scores_gemma":[0.00003911098,0.00007025398,0.0001033413,0.0000922162,0.00000708194,0.0001670265,0.000001064869,0.0002192828,6.112385e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005023256,"about_ca_system_score_gemma":0.0000232297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001692931,"about_ca_topic_score_gemma":0.00001342485,"domain_scores_codex":[0.999358,0.000002124382,0.0002996349,0.00005025135,0.0001295542,0.0001604637],"domain_scores_gemma":[0.9995829,0.0001479123,0.00007445936,0.00009202639,0.000053191,0.000049479],"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":[0.000007271084,0.000005011861,0.000008817134,0.0000296568,0.00004320396,0.000003177648,0.0006315463,0.9967898,0.0005295945,0.001346931,0.0001121332,0.0004928209],"study_design_scores_gemma":[0.004899649,0.0001847297,0.009459808,0.0003944921,0.0005106857,0.0000630014,0.001148111,0.8632192,0.02957381,0.003755794,0.08607682,0.0007138954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006314712,0.0008266348,0.9916843,0.000403836,0.0005568233,0.0001163961,0.00001071566,0.00007248524,0.00001406827],"genre_scores_gemma":[0.9698143,0.0002427984,0.02959558,0.00003601801,0.0002513551,0.000005145546,0.000008148607,0.00003127533,0.00001535434],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9634996,"threshold_uncertainty_score":0.2864874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009354651810222181,"score_gpt":0.2077911597719373,"score_spread":0.1984365079617151,"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."}}