{"id":"W2102228437","doi":"10.1146/annurev-environ-072811-114530","title":"Methods and Global Environmental Governance","year":2013,"lang":"en","type":"article","venue":"Annual Review of Environment and Resources","topic":"Sustainability and Climate Change Governance","field":"Environmental Science","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Toolbox; Variety (cybernetics); Management science; Corporate governance; Computer science; Data science; Environmental governance; Field (mathematics); Environmental planning; Environmental science; Business; Engineering; Artificial intelligence","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":[0.0003503386,0.0001776851,0.0002792991,0.000004206449,0.00008303085,0.00001219972,0.0001529369,0.00005503975,0.0046696],"category_scores_gemma":[0.00004933312,0.0001386441,0.00005779245,0.00005502845,0.0007004084,0.0002550514,0.0004364687,0.00007243684,0.0001110962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009406052,"about_ca_system_score_gemma":0.000001524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001614426,"about_ca_topic_score_gemma":0.00000289471,"domain_scores_codex":[0.9987308,0.0001171801,0.0002818976,0.0003548162,0.0002800958,0.0002352186],"domain_scores_gemma":[0.9993936,0.0000667377,0.0001835155,0.000231492,0.000001643737,0.0001229501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00002466552,0.0002956636,0.2140919,0.002549452,0.0000489482,0.000006786709,0.003934332,0.00001177122,0.002171681,0.0002618544,0.007389292,0.7692137],"study_design_scores_gemma":[0.0001967651,0.0001320562,0.591077,0.0003917223,0.0000410104,0.00001565371,0.002055472,0.00002515554,0.0001569407,0.0006999205,0.4049711,0.0002371758],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8743806,0.1192347,0.00002049122,0.001239106,0.00002104873,0.0004214355,0.00005889939,0.000009130657,0.00461466],"genre_scores_gemma":[0.5146608,0.4782388,0.004122228,0.001649043,0.00003571532,0.00008082241,0.000007234374,0.00001581214,0.001189558],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7689765,"threshold_uncertainty_score":0.9962403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006183792613215696,"score_gpt":0.2601583668812083,"score_spread":0.2539745742679926,"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."}}