{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009427012,0.00007552525,0.00005705675,0.00002154136,0.00008092414,0.00001351594,0.00009400322,0.00002983767,0.0001398518],"category_scores_gemma":[0.000002565088,0.00004895183,0.00003135899,0.00007109087,0.00001368452,0.00005140787,0.000002382374,0.0001344703,0.00007869225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001490432,"about_ca_system_score_gemma":0.000003887373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001903793,"about_ca_topic_score_gemma":0.00003920693,"domain_scores_codex":[0.9996526,0.00001081668,0.00007582817,0.00005623597,0.00007024583,0.0001342216],"domain_scores_gemma":[0.9997962,0.00003008036,0.000005181973,0.0001261859,0.000004151037,0.00003826219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002471136,0.00003930919,0.0009069504,0.0000443491,0.00003709899,0.000004187168,0.003030725,0.1367929,0.02943473,0.0009619892,0.001785749,0.8269373],"study_design_scores_gemma":[0.0004936544,0.00003754884,0.01467185,0.00005040274,0.00001313379,0.00002679935,0.00006255489,0.7716243,0.004063024,0.0001016609,0.2086198,0.0002353364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9591416,0.0001336753,0.0009950774,0.001718995,0.00006970501,0.00005544316,0.000007801576,0.0001837203,0.03769401],"genre_scores_gemma":[0.9983886,0.00003394168,0.0006043905,0.0002407661,0.000274289,0.00000310762,0.000001887369,0.00001574777,0.0004372584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8267019,"threshold_uncertainty_score":0.1996198,"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."}}