{"id":"W3125294869","doi":"10.1787/235683015007","title":"Energy and Greenhouse Impacts of Biofuels: A Framework for Analysis","year":2008,"lang":"en","type":"preprint","venue":"eScholarship (California Digital Library)","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Resources Canada; National Science Foundation","keywords":"Biofuel; Greenhouse gas; Natural resource economics; Land use; Land use, land-use change and forestry; Climate change; Resource (disambiguation); Environmental science; Environmental economics; Life-cycle assessment; Environmental resource management; Production (economics); Economics; Engineering; Waste management; Computer science; Civil engineering; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008512435,0.0004816779,0.0006893264,0.0006399283,0.00006706032,0.0004157715,0.0003745445,0.0007756536,0.00008615621],"category_scores_gemma":[0.0001008479,0.0004559405,0.0005307468,0.0006587754,0.0001404698,0.0008806251,0.0004164953,0.0005556438,0.00002537024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003269521,"about_ca_system_score_gemma":0.00005873333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007638251,"about_ca_topic_score_gemma":0.000001373725,"domain_scores_codex":[0.9981821,0.00003182236,0.0005747571,0.0005790892,0.0002487515,0.0003834924],"domain_scores_gemma":[0.9987191,0.0001206979,0.0001901894,0.0006037896,0.00005231589,0.0003139254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002647171,0.002170233,0.6084569,0.03704756,0.02799318,0.0001845452,0.0008373962,0.006764237,0.003979269,0.009216412,0.04602771,0.2546754],"study_design_scores_gemma":[0.002131751,0.0004354567,0.007818781,0.001255627,0.002164454,0.00005253166,0.000108656,0.02177088,0.09092727,0.2154192,0.6534248,0.004490544],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.912725,0.008844598,0.04820922,0.0005863496,0.0009810856,0.0009169424,0.02338199,0.002014568,0.002340219],"genre_scores_gemma":[0.9877459,0.002615072,0.007171566,0.0001484802,0.000273546,0.00003284429,0.001745537,0.0001302802,0.0001367514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6073971,"threshold_uncertainty_score":0.9997892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01726470646884962,"score_gpt":0.2176010282534857,"score_spread":0.2003363217846361,"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."}}