{"id":"W589529638","doi":"","title":"INCREASING THE 'GREEN' ON MASS TRANSIT MACHINES","year":2005,"lang":"en","type":"article","venue":"Trains","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Miami; Biodiesel; Diesel fuel; Transit (satellite); Automotive engineering; Environmental science; Power (physics); Engineering; Transport engineering; Marine engineering; Meteorology; Public transport; Geography; Physics","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":[0.000652301,0.0006167082,0.0001920721,0.0007522997,0.0006721693,0.0008375044,0.0004992994,0.0006708896,0.01596087],"category_scores_gemma":[0.00164667,0.0001317188,0.0002416267,0.0005973821,0.0005148044,0.001682419,0.0009578956,0.0004141323,0.003964482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000804289,"about_ca_system_score_gemma":0.0005928588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002533884,"about_ca_topic_score_gemma":0.007400313,"domain_scores_codex":[0.9993155,0.0001299928,0.00001079765,0.00005639238,0.0003647505,0.0001224871],"domain_scores_gemma":[0.9987916,0.0002086319,0.0001285541,0.0001171804,0.0006657654,0.00008817734],"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":[0.00119438,0.0006351033,0.02222462,0.0008453713,0.00005697138,0.0004257713,0.001417562,0.01633853,0.09831905,0.01766207,0.03916738,0.8017132],"study_design_scores_gemma":[0.0001234654,0.003594479,0.1536773,0.00055511,0.0001855862,0.0008031048,0.003265735,0.02020768,0.1526258,0.01930897,0.6455429,0.000109946],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7181246,0.001939213,0.03834726,0.005340099,0.0004480238,0.0001591132,0.0003488401,0.001987993,0.2333048],"genre_scores_gemma":[0.911504,0.001237256,0.01473582,0.001019194,0.0002401699,0.00004341404,0.000302483,0.0003777159,0.07053996],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01596087,"threshold_uncertainty_score":0.05339444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01250177747886931,"score_gpt":0.2205702265552378,"score_spread":0.2080684490763685,"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."}}