{"id":"W4410016948","doi":"10.1071/mf24287","title":"Ramsar on repeat: quantifying US policy action by political party","year":2025,"lang":"en","type":"article","venue":"Marine and Freshwater Research","topic":"Policy Transfer and Learning","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political action; Politics; Action (physics); Political science; Biology; Fishery; Ecology; Law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002886218,0.0003397151,0.0003950094,0.002951997,0.0004982033,0.001372852,0.0007077786,0.0006835086,0.005503206],"category_scores_gemma":[0.01874022,0.0001125624,0.0005405471,0.00504669,0.0006599926,0.00138883,0.002098913,0.001082139,0.0012258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001202955,"about_ca_system_score_gemma":0.0009474169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02556443,"about_ca_topic_score_gemma":0.02492644,"domain_scores_codex":[0.9966215,0.001501489,0.000257164,0.0005222973,0.0007477911,0.0003497544],"domain_scores_gemma":[0.9881456,0.004990917,0.004060356,0.001219071,0.001178977,0.0004051351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002782063,0.0002792624,0.8586574,0.000313053,0.000563433,0.0001269397,0.002015771,0.01119645,0.000565812,0.01982003,0.04416981,0.06201376],"study_design_scores_gemma":[0.00005141857,0.0003121604,0.8785242,0.0001978014,0.0001522523,0.0001432263,0.00674425,0.01540284,0.001292651,0.008682641,0.08841132,0.00008516482],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8918012,0.0006978155,0.003928641,0.001971982,0.00008736151,0.0001570295,0.03173464,0.0003286059,0.06929267],"genre_scores_gemma":[0.9589689,0.0002930982,0.00317753,0.0005082054,0.0001046545,0.0003668647,0.03133119,0.00009687139,0.005152757],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02556443,"threshold_uncertainty_score":0.05083126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1845915868253628,"score_gpt":0.4992792703952999,"score_spread":0.3146876835699371,"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."}}