{"id":"W7133025559","doi":"","title":"Accounting for Variability and Uncertainty in Life Cycle Assessments: Oil Sands Case Studies","year":2019,"lang":"","type":"dissertation","venue":"TSpace","topic":"Global Energy and Sustainability Research","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hudbay Minerals (Canada); Alberta Energy","funders":"Argonne National Laboratory; Canada's Oil Sands Innovation Alliance; Carbon Management Canada; Canadian Natural Resources Limited; U.S. Environmental Protection Agency; U.S. Department of Energy","keywords":"Greenhouse gas; Life-cycle assessment; Refinery; Oil sands; Oil refinery; Fugitive emissions; Upstream (networking); Asphalt; Production (economics)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006601798,0.0008464153,0.0007393221,0.001739693,0.0007490744,0.001596655,0.001324794,0.001638678,0.0008157997],"category_scores_gemma":[0.01079534,0.0004571727,0.001619794,0.002354981,0.0008212161,0.001494664,0.001190821,0.001326167,0.0000788436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003030825,"about_ca_system_score_gemma":0.001699521,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03793171,"about_ca_topic_score_gemma":0.03312074,"domain_scores_codex":[0.9981021,0.0009437181,0.00009913457,0.000225191,0.0004233299,0.0002065052],"domain_scores_gemma":[0.9864702,0.01099525,0.0008138292,0.0006766799,0.0008083196,0.0002356613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001436873,0.0001275687,0.01995739,0.00005431188,0.0001096415,0.0005589865,0.0001480874,0.9693025,0.0004645858,0.002557361,0.0002743329,0.006301655],"study_design_scores_gemma":[0.00004379174,0.000206532,0.009804326,0.00003623385,0.00008431594,0.000136002,0.0004718765,0.9806871,0.002418824,0.004853949,0.001206376,0.00005058973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831179,0.0002095103,0.01214137,0.0003022022,0.000007729258,0.00009692374,0.0008524797,0.00005407785,0.003217757],"genre_scores_gemma":[0.9911087,0.0001006014,0.007924566,0.00001745637,0.000007410691,0.00003781682,0.0003341573,0.00001458112,0.0004546449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9620683,"threshold_uncertainty_score":0.07542187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03063805478442105,"score_gpt":0.413386995228228,"score_spread":0.382748940443807,"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."}}