{"id":"W4408723695","doi":"10.1021/acs.est.4c12667","title":"Emission Factor Recommendation for Life Cycle Assessments with Generative AI","year":2025,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Factor (programming language); Generative grammar; Life-cycle assessment; Environmental science; Computer science; Artificial intelligence; 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":[0.001727488,0.00169669,0.00102227,0.00346042,0.0007901486,0.00140745,0.002344984,0.001591646,0.008771311],"category_scores_gemma":[0.01430781,0.0006604717,0.001402605,0.002143694,0.0006067033,0.001749011,0.001030483,0.001737616,0.002202883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00143203,"about_ca_system_score_gemma":0.001905519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01501533,"about_ca_topic_score_gemma":0.04059564,"domain_scores_codex":[0.9983984,0.0004545025,0.0001266662,0.0004461369,0.0004864364,0.00008797173],"domain_scores_gemma":[0.9915947,0.006430924,0.0002990957,0.0005960738,0.0009863209,0.00009291869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000291766,0.0003760864,0.009808565,0.0006845595,0.0002576554,0.0003889874,0.0003756482,0.3142003,0.005349095,0.009587688,0.01881113,0.6398685],"study_design_scores_gemma":[0.00002603655,0.00002843576,0.0005587418,0.0000519858,0.00003255833,0.00004935986,0.00003764936,0.9817646,0.001620199,0.01160881,0.00420452,0.00001718369],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0293453,0.001296114,0.9462026,0.0008827368,0.0001295521,0.0004174813,0.00216695,0.009623723,0.009935546],"genre_scores_gemma":[0.3938761,0.0004272049,0.5934681,0.0008786122,0.0001499973,0.0005241357,0.005189445,0.0005755912,0.004910753],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01501533,"threshold_uncertainty_score":0.02985585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00711622386209644,"score_gpt":0.296181625688844,"score_spread":0.2890654018267476,"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."}}