{"id":"W2129300499","doi":"10.1002/atr.113","title":"Level of service analysis for airport baggage claim with a case study of the Calgary International Airport","year":2010,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"International airport; Multidimensional scaling; Service (business); Work (physics); Transport engineering; Function (biology); Regression analysis; Operations research; Data collection; Computer science; Engineering; Business; Statistics; Marketing; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004103821,0.00009692802,0.0004386504,0.0003521754,0.00006219777,0.000008259852,0.000186449,0.00006226968,0.00009816774],"category_scores_gemma":[0.0000240287,0.00007574455,0.0002668598,0.0007319222,0.00002561395,0.0003214054,0.000002917779,0.0002167512,2.682586e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001929039,"about_ca_system_score_gemma":0.00004345724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003349255,"about_ca_topic_score_gemma":0.008810413,"domain_scores_codex":[0.9984784,0.000008199508,0.001167751,0.0001455186,0.0001217656,0.00007837074],"domain_scores_gemma":[0.9967695,0.00004289439,0.002444721,0.0002003383,0.000501199,0.00004128771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000161059,0.0005245372,0.9196076,0.00002200739,0.001537548,0.0000466474,0.00271101,0.07235105,0.0001591909,0.002224555,0.000007227361,0.000647557],"study_design_scores_gemma":[0.001871635,0.0002368284,0.9915691,0.00001266828,0.000650074,0.00004438389,0.003621131,0.0008486292,0.0002767175,0.0004760305,0.0002940908,0.00009870608],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802873,0.00001811496,0.01879215,0.0002278223,0.0002344049,0.000139879,0.0001988191,0.000002154095,0.00009931474],"genre_scores_gemma":[0.9966547,0.000005366214,0.003125976,0.00003299268,0.00004775577,0.000008531388,0.00003205052,0.000009490076,0.00008317561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0719615,"threshold_uncertainty_score":0.4916417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05897460313922227,"score_gpt":0.2757228243157555,"score_spread":0.2167482211765333,"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."}}