{"id":"W4389623701","doi":"10.1287/deca.2023.intro.v20.n4","title":"Decision Analysis to Advance Environmental Sustainability","year":2023,"lang":"en","type":"article","venue":"Decision Analysis","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Sustainability; Decision analysis; Sustainability science; Scope (computer science); Sustainability organizations; Status quo; Decision support system; Environmental resource management; Risk analysis (engineering); Management science; Business; Computer science; Environmental planning; Environmental economics; Economics; Ecology; Environmental science","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001462475,0.0002230498,0.0007803653,0.002627961,0.0002030969,0.00008811376,0.0003794227,0.0001133881,0.005340756],"category_scores_gemma":[0.0003743784,0.0002549865,0.0008634198,0.005487784,0.00005099916,0.0002847779,0.0002604342,0.0001026926,0.01050256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007268109,"about_ca_system_score_gemma":0.000007917447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001230965,"about_ca_topic_score_gemma":0.0001558984,"domain_scores_codex":[0.9973717,0.00002820708,0.001028047,0.001017646,0.0001534802,0.0004008764],"domain_scores_gemma":[0.9981708,0.0002882825,0.0002734103,0.001009224,0.00001483132,0.000243456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003396647,0.00008700638,0.7878358,0.000001606172,0.001256606,0.000006083347,0.0001867296,0.187282,0.00001435814,0.001414708,0.0008431203,0.02103796],"study_design_scores_gemma":[0.0002676848,0.00003167883,0.9052906,0.000001320562,0.0005180489,2.905974e-7,0.0003026632,0.06206754,0.00002009155,0.02102976,0.01018672,0.0002836073],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7942652,0.0001595404,0.204089,0.0002816054,0.0001182958,0.0001830699,0.0001866307,0.00005517396,0.0006615788],"genre_scores_gemma":[0.9938167,0.0002199202,0.003605616,0.0002362302,0.00003165652,0.00004511833,0.0002689529,0.00002158113,0.001754165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2004834,"threshold_uncertainty_score":0.9999902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03707153982529466,"score_gpt":0.2581202507130723,"score_spread":0.2210487108877776,"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."}}