{"id":"W2089422147","doi":"10.3846/16484142.2013.785019","title":"EFFICIENCY EVALUATION IN PUBLIC ROAD TRANSPORT: A STOCHASTIC FRONTIER ANALYSIS","year":2013,"lang":"en","type":"article","venue":"Transport","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Stochastic frontier analysis; Investment (military); Frontier; Public transport; Profit (economics); Sample (material); Transport engineering; Environmental economics; Business; Econometrics; Industrial organization; Economics; Engineering; Microeconomics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.008320361,0.0003252614,0.0008856282,0.003064503,0.0001816457,0.0001586182,0.001274952,0.0001809882,0.008944831],"category_scores_gemma":[0.0006296395,0.0002589451,0.0006809025,0.01208188,0.0002200485,0.0009447798,0.00001327744,0.0002945408,0.0009696371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000149158,"about_ca_system_score_gemma":0.0003348631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001603347,"about_ca_topic_score_gemma":0.00411526,"domain_scores_codex":[0.9915656,0.0003568929,0.001810796,0.001214655,0.004335815,0.0007162123],"domain_scores_gemma":[0.9968637,0.0002853951,0.0003514354,0.001280486,0.0009620404,0.0002570071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002815295,0.0008249277,0.5441371,0.000006114108,0.0003311424,0.00002118946,0.003568033,0.3867852,0.0003007937,0.0003925434,0.000233775,0.06337102],"study_design_scores_gemma":[0.0004606174,0.00002804996,0.6862018,0.000007038668,0.0005854277,0.000001073856,0.0003608508,0.3099259,0.00001057709,0.002004948,0.0001594569,0.0002542297],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7897393,0.0002009675,0.2045568,0.0008578416,0.0001777766,0.000590227,0.00001315486,0.0000647028,0.00379923],"genre_scores_gemma":[0.9983059,0.000003360645,0.0004877639,0.0001418045,0.00003521202,0.0001211235,0.00007050901,0.00001949851,0.0008148652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2085666,"threshold_uncertainty_score":0.9999863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07946227745493478,"score_gpt":0.35098403134698,"score_spread":0.2715217538920452,"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."}}