{"id":"W3024876273","doi":"10.1016/j.jclepro.2020.122061","title":"A new integrated framework to estimate the climate change impacts of biomass utilization for biofuel in life cycle assessment","year":2020,"lang":"en","type":"article","venue":"Journal of Cleaner Production","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"National Key Research and Development Program of China; Young Scientists Fund; National Natural Science Foundation of China","keywords":"Greenhouse gas; Biofuel; Environmental science; Life-cycle assessment; Fossil fuel; Climate change; Land use, land-use change and forestry; Carbon sequestration; Biomass (ecology); Global warming; Climate change mitigation; Renewable energy; Natural resource economics; Environmental engineering; Waste management; Land use; Engineering; Carbon dioxide; Production (economics); Agronomy; Ecology; Economics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002853666,0.0008928282,0.0008423176,0.001541386,0.0005964641,0.002517186,0.00138401,0.001211357,0.002120303],"category_scores_gemma":[0.00317152,0.0004976469,0.001376292,0.00121188,0.0005502236,0.002548692,0.001873913,0.000985502,0.000281161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002336134,"about_ca_system_score_gemma":0.003378218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04183887,"about_ca_topic_score_gemma":0.0331281,"domain_scores_codex":[0.9991309,0.0002844408,0.00005248946,0.0001644434,0.0002690972,0.00009864645],"domain_scores_gemma":[0.9990646,0.0002863832,0.000101388,0.0001066132,0.0003842731,0.00005677219],"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":[0.00003778604,0.00006780672,0.002602341,0.0000396125,0.0002466468,0.00006069247,0.00002893291,0.9495571,0.001714003,0.02498039,0.0007832302,0.01988143],"study_design_scores_gemma":[0.00001315759,0.00003185771,0.00140386,0.00001620629,0.00006837001,0.00001740197,0.00003014738,0.9735948,0.000721616,0.02061788,0.003465969,0.00001860979],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0545754,0.0005239161,0.9318947,0.0005265679,0.0001030406,0.0001394522,0.001545948,0.0004290512,0.01026186],"genre_scores_gemma":[0.7550444,0.000503852,0.2373236,0.0002097643,0.00007212417,0.0003094872,0.002012372,0.0001304928,0.004393961],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04183887,"threshold_uncertainty_score":0.08319068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04632382436971772,"score_gpt":0.3273523233750694,"score_spread":0.2810284990053517,"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."}}