{"id":"W4406241954","doi":"10.1016/j.patter.2024.101151","title":"Why the Environmental Data & Governance Initiative is archiving public environmental data","year":2025,"lang":"en","type":"article","venue":"Patterns","topic":"Environmental Justice and Health Disparities","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"New Venture Fund; Bloomberg Philanthropies; Bloomberg Family Foundation","keywords":"Accountability; Politics; Data governance; Corporate governance; Democracy; Environmental governance; Environmental justice; Environmental data; Political science; Public administration; Good governance; Business; Public relations; Environmental resource management; Data quality; Economics; Law","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":[0.0006154741,0.000174691,0.0001605895,0.00002911529,0.001156208,0.0001748651,0.002587744,0.00006998493,0.002717619],"category_scores_gemma":[0.00009456505,0.0001532197,0.00003494263,0.00007445885,0.0006656853,0.001018992,0.002449866,0.0003138338,0.0002940717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002403442,"about_ca_system_score_gemma":0.00008323502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002384149,"about_ca_topic_score_gemma":0.01662833,"domain_scores_codex":[0.9977264,0.0002812751,0.0002707843,0.0006160581,0.0005632265,0.0005422814],"domain_scores_gemma":[0.9977108,0.0003782692,0.0001351719,0.001652348,0.000001388252,0.0001220673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001327932,0.0003373294,0.8011495,0.0001120292,0.0001007532,0.000006750382,0.01645514,0.000001215084,0.00009031811,0.001829029,0.1633884,0.01651625],"study_design_scores_gemma":[0.0001580646,0.00000775937,0.3105583,0.00007466761,0.0000468827,7.415111e-7,0.01145428,0.00008165173,0.00001394159,0.0001426136,0.6773037,0.0001573574],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6394187,0.01012053,0.007451363,0.2307766,0.002162243,0.002171196,0.05916366,0.0001978574,0.04853787],"genre_scores_gemma":[0.9482108,0.01260051,0.0001260797,0.03514329,0.0002872286,0.00002597614,0.001871501,0.0000164524,0.00171818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5139153,"threshold_uncertainty_score":0.998194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1269500791036187,"score_gpt":0.3526134619267645,"score_spread":0.2256633828231458,"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."}}