{"id":"W4383873947","doi":"10.3167/reco.2023.130201","title":"Policy innovation through local, sustainable development evaluation","year":2023,"lang":"en","type":"article","venue":"Regions & Cohesion","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pledge; Summit; Operationalization; Earth Summit; Biodiversity; Politics; Sustainable development; Political science; Environmental planning; Climate change; Geography; Environmental protection; Environmental resource management; Public administration; Law; Environmental science; Physical geography; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005496852,0.0001290498,0.0001006105,0.0001196004,0.0005286126,0.00003431868,0.0001406978,0.00008284274,0.0004212667],"category_scores_gemma":[0.00008452901,0.000121668,0.00002609866,0.002369625,0.0001334272,0.0005002458,0.0002549391,0.00008403913,0.001811973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001433803,"about_ca_system_score_gemma":0.0001120819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006086425,"about_ca_topic_score_gemma":0.00002607501,"domain_scores_codex":[0.998381,0.00008006727,0.00023196,0.0002537107,0.0006605387,0.000392789],"domain_scores_gemma":[0.999607,0.00002717802,0.00009163182,0.0001982604,0.00002085408,0.00005505121],"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":[0.00008031868,0.001024171,0.07656175,0.00009650976,0.00009364561,0.0000905608,0.02224504,0.01759191,0.03318311,0.0545213,0.1649577,0.629554],"study_design_scores_gemma":[0.001078845,0.0001269713,0.7301967,0.00005449572,0.0000368139,0.000006319754,0.01100334,0.003807057,0.00980792,0.05411544,0.1891378,0.0006283496],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9674764,0.000009804669,0.005172084,0.001520729,0.0000712622,0.0005237934,0.000001115665,0.0001464816,0.02507834],"genre_scores_gemma":[0.9903412,0.0000554516,0.0005758438,0.0004088684,0.00004860362,0.00008556942,0.0001170523,0.00001772643,0.008349617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6536349,"threshold_uncertainty_score":0.9989652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04535377403154564,"score_gpt":0.3424917487397376,"score_spread":0.297137974708192,"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."}}