{"id":"W3044606135","doi":"10.1002/pan3.10124","title":"Levers and leverage points for pathways to sustainability","year":2020,"lang":"en","type":"article","venue":"People and Nature","topic":"Sustainability and Climate Change Governance","field":"Environmental Science","cited_by":313,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; Fisheries and Oceans Canada; McGill University; Western Forest Products; University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Environment and Climate Change Canada; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; AgBioResearch, Michigan State University; National Science Foundation","keywords":"Sustainability; Deliberation; Business; Incentive; Leverage (statistics); Environmental economics; Economics; Environmental resource management; Public economics; Political science; Computer science; Microeconomics; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001327135,0.00009994572,0.0001220676,0.000006980797,0.0001253603,0.00002532445,0.00008747257,0.0001105593,0.0001541373],"category_scores_gemma":[0.0005177475,0.00009033934,0.00002840497,0.0001515691,0.00005327403,0.0001333996,0.0001899575,0.0001472451,0.000006495709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009616823,"about_ca_system_score_gemma":0.00001186175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006877829,"about_ca_topic_score_gemma":0.0002605485,"domain_scores_codex":[0.9992182,0.00001670882,0.00007851249,0.0003520132,0.0001127647,0.0002217736],"domain_scores_gemma":[0.9995924,0.00007794076,0.0000230329,0.0001081052,0.00001739401,0.0001811693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001733386,0.0003058342,0.599613,0.001947064,0.00004851685,0.00004872199,0.2322122,0.0001945349,0.005137562,0.005925665,0.08606002,0.06677353],"study_design_scores_gemma":[0.001101423,0.0004561123,0.8063422,0.00000899529,0.0000261362,0.000007114571,0.02560395,0.0005904427,0.001527435,0.01481748,0.1490438,0.000474962],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9777908,0.0001762292,0.000144365,0.02105993,0.00003522441,0.0004578171,0.00006063635,0.00002439665,0.0002505605],"genre_scores_gemma":[0.9945121,0.0000462462,0.000274883,0.004990485,0.00003911123,0.00003104689,0.000004909524,0.00000727731,0.00009388843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2067292,"threshold_uncertainty_score":0.3683932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01242906584011651,"score_gpt":0.2343169582774433,"score_spread":0.2218878924373268,"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."}}