{"id":"W2998446550","doi":"","title":"An examination of heavy-duty trucks drivetrain options to reduce GHG emissions in British Columbia","year":2019,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Truck; Drivetrain; Heavy duty; Greenhouse gas; Automotive engineering; Global-warming potential; Environmental science; Business; Engineering","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":[0.0005387266,0.0002895766,0.000296654,0.001164573,0.002794387,0.002150582,0.001295022,0.0005647081,0.003074809],"category_scores_gemma":[0.0008994049,0.0002512433,0.00032037,0.00221484,0.0006089816,0.0004137223,0.0005744754,0.0007043784,0.000213881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03316793,"about_ca_system_score_gemma":0.03059639,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9880732,"about_ca_topic_score_gemma":0.9975649,"domain_scores_codex":[0.9992748,0.00006828069,0.00002163896,0.00004899536,0.0002967016,0.00028957],"domain_scores_gemma":[0.9989452,0.0001022556,0.0000498784,0.00001394864,0.0007511462,0.0001375744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002040216,0.001762594,0.6761972,0.001112376,0.0004720169,0.003185736,0.00882106,0.01845691,0.02366608,0.00803664,0.02386837,0.2323807],"study_design_scores_gemma":[0.00005260479,0.0003642772,0.9193253,0.000233137,0.0001462775,0.0001311606,0.03204349,0.004692405,0.00296784,0.0003558917,0.03962144,0.00006605063],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9600502,0.0009843088,0.0001467502,0.0008047635,0.00001679913,0.0001086561,0.000693909,0.00001571366,0.03717885],"genre_scores_gemma":[0.9759995,0.001139082,0.0003256528,0.0003338323,0.00000247971,0.00002882238,0.000354271,0.00001082259,0.02180559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03316793,"threshold_uncertainty_score":0.2406513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02222301035387804,"score_gpt":0.2724645149444851,"score_spread":0.2502415045906071,"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."}}