{"id":"W2072190049","doi":"10.1021/es101187h","title":"Assessing GHG Emissions, Ecological Footprint, and Water Linkage for Different Fuels","year":2010,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Water-Energy-Food Nexus Studies","field":"Environmental Science","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Greenhouse gas; Ecological footprint; Environmental science; Linkage (software); Environmental protection; Carbon footprint; Environmental engineering; Natural resource economics; Ecology; Sustainability; Chemistry; Economics","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":[0.001168806,0.0005350219,0.0003555742,0.002154797,0.0004514998,0.0007501399,0.0003950702,0.0005957417,0.001532683],"category_scores_gemma":[0.001443108,0.0001770018,0.0008524412,0.003940208,0.0003847628,0.001494503,0.0007069794,0.0002613811,0.0001427334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001444853,"about_ca_system_score_gemma":0.0005492106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01536323,"about_ca_topic_score_gemma":0.03761502,"domain_scores_codex":[0.9991577,0.0002136913,0.0000409852,0.00009246487,0.0004157847,0.00007944803],"domain_scores_gemma":[0.9993851,0.0003686002,0.00005891711,0.00002898751,0.0001378576,0.00002048727],"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":[0.002113421,0.0008272853,0.5256032,0.00058568,0.001198624,0.0009801262,0.0005005019,0.2965798,0.04958492,0.005983458,0.0003814581,0.1156616],"study_design_scores_gemma":[0.00009370418,0.003611538,0.7177031,0.00005506589,0.000754101,0.0004119026,0.003229942,0.1456589,0.1097943,0.01214643,0.006399084,0.0001420492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916794,0.0001935749,0.002569505,0.0000234226,0.000002138426,0.00005373525,0.0006772995,0.000007481958,0.004793483],"genre_scores_gemma":[0.9953206,0.0002428342,0.002732645,0.000007849188,0.00000156929,0.00006228063,0.0006083106,0.000009639991,0.001014175],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01536323,"threshold_uncertainty_score":0.03054762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01047024100619005,"score_gpt":0.2381429423973228,"score_spread":0.2276727013911327,"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."}}