{"id":"W413727926","doi":"","title":"Modeling Transit Bus Emissions using MOVES: Validation of Default Distributions and Embedded Drive Cycles with Local Data","year":2015,"lang":"en","type":"article","venue":"Transportation Research Board 94th Annual MeetingTransportation Research Board","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Range (aeronautics); Transport engineering; Mode (computer interface); Public transport; Driving cycle; Service (business); Data collection; Level of service; Environmental science; Automotive engineering; Computer science; Engineering; Statistics; Mathematics; Business; Electric vehicle","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002169792,0.0005562932,0.0004060734,0.0005879536,0.0003461985,0.0007099637,0.00123059,0.0005095408,0.0006882957],"category_scores_gemma":[0.006296915,0.0003849913,0.0005645098,0.0005796694,0.0004360953,0.0009963285,0.0004964416,0.0005213403,0.0002106228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001183017,"about_ca_system_score_gemma":0.0008121728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07311302,"about_ca_topic_score_gemma":0.07938037,"domain_scores_codex":[0.9991466,0.0003753671,0.00005232116,0.0002314686,0.0001330928,0.0000612023],"domain_scores_gemma":[0.9975884,0.001350038,0.0002991873,0.0003268278,0.0003872879,0.00004816537],"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":[0.0001595288,0.000117343,0.09227339,0.00005686825,0.00009090216,0.0000699362,0.0001257324,0.8947725,0.0008775333,0.0008169379,0.0003617744,0.01027755],"study_design_scores_gemma":[0.00002775826,0.0001243616,0.03503278,0.00001780576,0.000027032,0.00003357597,0.0001439864,0.9616675,0.001909345,0.0004252615,0.0005708906,0.00001975618],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870228,0.0000338584,0.0108774,0.00003546077,0.000005898704,0.00003225032,0.0007798668,0.0001965355,0.001015864],"genre_scores_gemma":[0.9954562,0.00002131543,0.003189534,0.000009671427,0.000002792059,0.00002754198,0.0009966453,0.00002401578,0.0002720931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07311302,"threshold_uncertainty_score":0.1453749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1142856173804114,"score_gpt":0.3793464263947968,"score_spread":0.2650608090143854,"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."}}