{"id":"W2607633755","doi":"10.1080/14719037.2017.1320043","title":"Toward precision governance: infusing data into public management of environmental hazards","year":2017,"lang":"en","type":"article","venue":"Public Management Review","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Biodesign Institute, Arizona State University; Arizona State University; Arizona Department of Health Services; Minnesota Department of Health; National Science Foundation","keywords":"Preparedness; Corporate governance; Hazard; Perspective (graphical); Data governance; Business; Environmental resource management; Environmental planning; Political science; Public relations; Economics; Computer science; Environmental science; Finance; Marketing; Data quality","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07300615,0.0009686743,0.001810215,0.005791792,0.001995339,0.01298353,0.003520025,0.007728111,0.002357417],"category_scores_gemma":[0.1082243,0.0009851707,0.001652469,0.007373081,0.01477713,0.02783092,0.01062225,0.01316376,0.0006531457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006153018,"about_ca_system_score_gemma":0.02482725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005807661,"about_ca_topic_score_gemma":0.006810122,"domain_scores_codex":[0.951519,0.03390822,0.003054771,0.002143731,0.008078906,0.001295404],"domain_scores_gemma":[0.8474342,0.1174337,0.008480032,0.01264116,0.0117079,0.002303008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004241374,0.00006879704,0.001819487,0.01100305,0.0003753389,0.0001375102,0.003331275,0.003869644,0.0008275656,0.5983694,0.04312767,0.3370279],"study_design_scores_gemma":[0.00004168454,0.00009919795,0.001328252,0.02224807,0.0001706572,0.0001739156,0.00263197,0.001242863,0.0009105778,0.3804974,0.5905682,0.00008727465],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.003796375,0.5471109,0.07817717,0.3414644,0.005840614,0.0002437098,0.0002646787,0.0002518109,0.02285028],"genre_scores_gemma":[0.1447802,0.6855981,0.06891134,0.08787164,0.009187531,0.0006776981,0.0003233787,0.0001480878,0.002502088],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07300615,"threshold_uncertainty_score":0.386098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1622490435895744,"score_gpt":0.3620018580108955,"score_spread":0.1997528144213211,"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."}}