{"id":"W2746309342","doi":"10.1061/jtepbs.0000067","title":"Modeling Transit Bus Emissions Using <i>MOVES</i> : Comparison of Default Distributions and Embedded Drive Cycles with Local Data","year":2017,"lang":"en","type":"article","venue":"Journal of Transportation Engineering Part A Systems","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Environmental Protection Agency","keywords":"Transit (satellite); Range (aeronautics); Transport engineering; Mode (computer interface); Service (business); Driving cycle; Environmental science; Data collection; Public transport; Automotive engineering; Computer science; Engineering; Statistics; Mathematics; Business; Electric vehicle","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.000196624,0.0001568699,0.0003933582,0.00008391284,0.0001620901,0.00005572187,0.0002612874,0.0000806041,0.000002168763],"category_scores_gemma":[0.00001111333,0.0001323074,0.00004711923,0.00007411527,0.000036027,0.0005341728,0.000005204301,0.0002369717,1.503907e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002774934,"about_ca_system_score_gemma":0.00004210345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004339361,"about_ca_topic_score_gemma":0.00002730171,"domain_scores_codex":[0.9988147,0.000008104871,0.0006645066,0.000110959,0.0002360859,0.0001656133],"domain_scores_gemma":[0.9991398,0.00002593556,0.0002122499,0.0003393315,0.0001313372,0.0001513564],"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":[0.00001920646,0.00002032933,0.003405459,0.0002980221,0.00009107732,0.000008648955,0.0005855003,0.9877808,0.007439972,0.00002896037,0.00002941951,0.0002925984],"study_design_scores_gemma":[0.0004773035,0.00003639041,0.003429364,0.001148695,0.0001305641,0.00004790061,0.000442389,0.9924206,0.001305815,0.00000108295,0.0004092692,0.0001506032],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5187447,0.0005846469,0.480262,0.000009537816,0.00018422,0.00005590877,0.0001338434,0.00001921752,0.000005925522],"genre_scores_gemma":[0.9966886,0.00009382395,0.003046404,5.642976e-7,0.0000930157,0.000001862569,0.00004786519,0.00002538473,0.000002475631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4779439,"threshold_uncertainty_score":0.5395341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03903079056845272,"score_gpt":0.2810376750931157,"score_spread":0.242006884524663,"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."}}