{"id":"W2595256906","doi":"","title":"EVALUATION METHODS OF REGIONAL TRANSPORT SYSTEMS PERFORMANCE EFFICIENCY","year":2016,"lang":"en","type":"article","venue":"The Journal of Internet Banking and Commerce","topic":"Transportation Systems and Logistics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Data envelopment analysis; Context (archaeology); Set (abstract data type); Principal component analysis; Principal (computer security); Service (business); Operations research; Basis (linear algebra); Data set; Data mining; Artificial intelligence; Mathematical optimization","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":[0.002503349,0.0000645679,0.0001524462,0.00005132832,0.00001807745,0.000004886007,0.0001302482,0.00002908467,0.00001769955],"category_scores_gemma":[0.00001322709,0.00003290246,0.00003587694,0.00005103736,0.00004532501,0.00006521463,0.000002419132,0.00008235327,6.028446e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002229013,"about_ca_system_score_gemma":0.00001596214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002137073,"about_ca_topic_score_gemma":0.000003331478,"domain_scores_codex":[0.9991122,0.0001232343,0.0004063482,0.0000321104,0.0002569034,0.00006917123],"domain_scores_gemma":[0.9993691,0.000175155,0.0001601583,0.00007951957,0.0001943697,0.00002172443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003760229,0.0001221261,0.04181325,0.001103773,0.0008994736,0.000006717648,0.02394005,0.1888316,0.04707039,0.006478846,0.002316172,0.6870416],"study_design_scores_gemma":[0.005449281,0.001492635,0.4704638,0.01076821,0.001481949,0.001535102,0.003288826,0.4593385,0.0170144,0.0008253094,0.02746669,0.0008753547],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7119241,0.001896033,0.2853473,0.00004643961,0.0002693322,0.00004434544,0.000001456257,0.000007877881,0.0004631007],"genre_scores_gemma":[0.999086,0.0004488708,0.000340666,0.000008778948,0.00005245627,0.000001002633,2.92617e-7,0.000007166959,0.0000547828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6861662,"threshold_uncertainty_score":0.1341723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04641978530154926,"score_gpt":0.2925420882995139,"score_spread":0.2461223029979646,"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."}}