{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002149008,0.0004794699,0.0003939697,0.002390239,0.001100018,0.001391789,0.001093589,0.0003980514,0.0006969559],"category_scores_gemma":[0.002902411,0.0002434335,0.0002519666,0.003354886,0.0003211247,0.000703898,0.0009570828,0.0004341533,0.0002912965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0105857,"about_ca_system_score_gemma":0.01098285,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8314946,"about_ca_topic_score_gemma":0.897953,"domain_scores_codex":[0.9987515,0.0002091079,0.0001165278,0.0002032105,0.0005206426,0.0001989874],"domain_scores_gemma":[0.9966928,0.0001423368,0.0001737804,0.0001622285,0.002694222,0.0001345737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006837599,0.0004526327,0.8308799,0.0002664417,0.0002804066,0.0005446613,0.001664675,0.04201644,0.01283458,0.01193814,0.01624352,0.08219487],"study_design_scores_gemma":[0.00004053685,0.0002523455,0.94261,0.00008920961,0.00006011144,0.00007353174,0.001984709,0.01792621,0.006634496,0.00115964,0.02909331,0.00007591902],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9226168,0.0009178332,0.01604816,0.0005762008,0.0000821919,0.0005966119,0.01803318,0.000277751,0.04085132],"genre_scores_gemma":[0.9485089,0.000536163,0.01975076,0.0002597988,0.00001839862,0.0006723346,0.02463438,0.00007373466,0.005545513],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1685054,"threshold_uncertainty_score":0.3389956,"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."}}