{"id":"W2337241705","doi":"10.1021/acs.est.5b01255","title":"Well-to-Wheels Greenhouse Gas Emissions of Canadian Oil Sands Products: Implications for U.S. Petroleum Fuels","year":2015,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Global Energy and Sustainability Research","field":"Energy","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Vehicle Technologies Office; Bioenergy Technologies Office; Biomass Program; Vehicle Technologies Program; Office of Energy Efficiency and Renewable Energy; European Commission","keywords":"Diesel fuel; Oil sands; Greenhouse gas; Gasoline; Asphalt; Environmental science; Oil refinery; Petroleum; Life-cycle assessment; Synthetic crude; Fuel oil; Waste management; Fossil fuel; Fugitive emissions; Environmental engineering; Unconventional oil; Engineering; Production (economics); Chemistry; Geology","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":[0.0003075947,0.0008397147,0.0002503376,0.00169887,0.001122887,0.001013264,0.0005256835,0.0002718968,0.0009031228],"category_scores_gemma":[0.0007386728,0.0002588486,0.0007494268,0.003196613,0.0003943621,0.0006958999,0.0004575376,0.0002940073,0.000122548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02110212,"about_ca_system_score_gemma":0.01170263,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9855457,"about_ca_topic_score_gemma":0.9921054,"domain_scores_codex":[0.9996763,0.00001546635,0.00000887258,0.00005866747,0.0001639086,0.00007681658],"domain_scores_gemma":[0.9996662,0.00002680596,0.00003250684,0.00001521274,0.0002325076,0.00002677296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002136836,0.00009375848,0.7275617,0.0004231295,0.0004442651,0.0003517785,0.0005894606,0.1627919,0.02267793,0.005248902,0.004845089,0.07475848],"study_design_scores_gemma":[0.00001221232,0.00003171536,0.9072304,0.00007100114,0.0001547665,0.00004950475,0.0008006436,0.06175577,0.01266657,0.001197868,0.01593662,0.00009291238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9703911,0.00124252,0.004661754,0.0004317122,0.00001126394,0.00006538605,0.01113415,0.0000994791,0.01196271],"genre_scores_gemma":[0.9888567,0.001377957,0.003773738,0.0000806751,0.000002655064,0.00002590068,0.003694382,0.00002650802,0.002161462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02110212,"threshold_uncertainty_score":0.1531073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01684201653125796,"score_gpt":0.2597204048422313,"score_spread":0.2428783883109733,"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."}}