{"id":"W599725933","doi":"","title":"ESTABLISHING A KYOTO BENCHMARK FOR HEAVY TRUCK FUEL CONSUMPTION IN MANITOBA","year":2002,"lang":"en","type":"article","venue":"","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Truck; Fuel efficiency; Diesel fuel; Environmental science; Scope (computer science); Consumption (sociology); Benchmark (surveying); Transport engineering; Waste management; Automotive engineering; Engineering; Agricultural economics; Computer science; Geography; Economics","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":[0.0001021275,0.00008512393,0.00009321564,0.00007840672,0.00003695923,0.00004589597,0.0000754919,0.00006063532,0.0007110299],"category_scores_gemma":[0.00001633043,0.00008067476,0.00002737576,0.0001039344,0.000007668988,0.0002761399,0.00001033603,0.00009782694,0.00005571363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004977993,"about_ca_system_score_gemma":0.000001788017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004300852,"about_ca_topic_score_gemma":0.0003673053,"domain_scores_codex":[0.9994552,0.000004794477,0.0001726178,0.0001000792,0.00006126933,0.000206084],"domain_scores_gemma":[0.999756,0.00005625474,0.0000107129,0.0001140479,0.00001046796,0.00005245503],"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":[0.00009568678,0.0002919194,0.3413789,0.002726754,0.00007117107,0.00002862334,0.00426231,0.06509915,0.009942678,0.003499143,0.1532153,0.4193884],"study_design_scores_gemma":[0.0007275559,0.00003117988,0.02240406,0.00008492228,0.000004359069,0.000008718188,0.0001391569,0.9185368,0.001170364,0.0001997123,0.05644994,0.0002432506],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786057,0.0006596354,0.00238051,0.00008221778,0.0002724634,0.0002483867,0.000007757028,0.0001820465,0.01756131],"genre_scores_gemma":[0.9957944,0.0003239413,0.003173797,0.00005532118,0.00008598682,0.00004662594,0.000006650205,0.00001614001,0.0004971127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8534377,"threshold_uncertainty_score":0.7785279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02980975070528051,"score_gpt":0.2262797573710677,"score_spread":0.1964700066657872,"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."}}