{"id":"W3130148376","doi":"10.1371/journal.pone.0246450","title":"Visualizing changes to US federal environmental agency websites, 2016–2020","year":2021,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Climate Change Communication and Perception","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"National Institute of Environmental Health Sciences; National Institutes of Health; Doris Duke Charitable Foundation; David and Lucile Packard Foundation","keywords":"Agency (philosophy); Data science; Environmental resource management; Political science; Environmental science; Computer science; Sociology","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":["insufficient_payload"],"category_scores_codex":[0.0001779051,0.00006786823,0.0001072056,0.00002888709,0.0004019458,0.000087377,0.0001558014,0.00005733062,0.02553257],"category_scores_gemma":[0.00007913175,0.00007966819,0.00002970455,0.0001414007,0.00004767992,0.00008706433,0.0001289886,0.00007679863,0.001631993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001262332,"about_ca_system_score_gemma":0.00003066268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003624125,"about_ca_topic_score_gemma":0.007572859,"domain_scores_codex":[0.9990653,0.0001731615,0.00009617897,0.0001642635,0.0003001808,0.0002008831],"domain_scores_gemma":[0.9995616,0.00004514062,0.00003337188,0.0002044569,0.00002417972,0.0001312625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002621282,0.002697255,0.0387721,0.00006586094,0.0001102667,0.00002115804,0.1086546,7.702458e-7,0.8131196,0.0007441883,0.01085462,0.02493329],"study_design_scores_gemma":[0.000801254,0.0002317728,0.1287359,0.0005150838,0.0001312479,0.000003189053,0.04010774,0.0001541243,0.02539253,0.0005258268,0.8023686,0.001032706],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9400887,0.0007179182,0.000008231568,0.01656194,0.00007581429,0.0001788684,0.00002196976,0.0000776778,0.04226889],"genre_scores_gemma":[0.9488496,0.02262485,0.001518577,0.004523988,0.0006855103,0.00005739271,0.0002115922,0.00002165511,0.02150686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.791514,"threshold_uncertainty_score":0.9991453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.420116056148829,"score_gpt":0.3965617519183189,"score_spread":0.02355430423051008,"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."}}