{"id":"W2583787078","doi":"10.1146/annurev-resource-100815-095513","title":"Life Cycle Assessment for Economists","year":2017,"lang":"en","type":"article","venue":"Annual Review of Resource Economics","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Externality; Life-cycle assessment; Product (mathematics); Product lifecycle; Product life-cycle management; Economics; Environmental economics; Risk analysis (engineering); Production (economics); Business; New product development; Microeconomics; Marketing","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000849116,0.0001428158,0.0003660855,0.000009710208,0.000239158,0.0000356472,0.000556799,0.00005671979,0.000937449],"category_scores_gemma":[0.00047947,0.0001370165,0.0002010043,0.00001085403,0.0003103801,0.0003644216,0.0003490422,0.00007785868,0.00007324162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002730031,"about_ca_system_score_gemma":0.00004034828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008846157,"about_ca_topic_score_gemma":0.00002162781,"domain_scores_codex":[0.9989648,0.00003052213,0.0004057701,0.0002862928,0.00006437073,0.0002481952],"domain_scores_gemma":[0.9984124,0.00006586633,0.0004419962,0.0008376238,0.000007001119,0.0002350937],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001470125,0.0007585798,0.3348993,0.007270411,0.0001952091,0.000003757396,0.0008451716,0.003830813,0.00005674912,0.004359647,0.1023905,0.5452428],"study_design_scores_gemma":[0.0003943413,0.0001258806,0.1489789,0.0001889416,0.00003379132,0.00000174082,0.0002075115,0.0007220185,0.00006543753,0.0009889363,0.8480652,0.0002273217],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8781731,0.00210934,0.0001250535,0.004486016,0.0001042403,0.001202096,0.000198589,0.00001662528,0.113585],"genre_scores_gemma":[0.9731107,0.01502891,0.003710926,0.005566976,0.0001277218,0.0001187592,0.00004025303,0.00004353871,0.002252252],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7456747,"threshold_uncertainty_score":0.9999758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009826310068318623,"score_gpt":0.2949390353411636,"score_spread":0.285112725272845,"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."}}