{"id":"W4408321629","doi":"10.1111/conl.13092","title":"A Survey of Mammal and Fish Genetic Diversity Across the Global Protected Area Network","year":2025,"lang":"en","type":"article","venue":"Conservation Letters","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-Leipzig; Universität Leipzig; U.S. Geological Survey; Deutsche Forschungsgemeinschaft","keywords":"Mammal; Fish <Actinopterygii>; Diversity (politics); Geography; Fishery; Marine mammal; Genetic diversity; Biodiversity; Ecology; Biology; Environmental resource management; Environmental science; Population; Political science","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001424005,0.00007073027,0.00007458001,0.000007119193,0.0002321657,0.00001893307,0.0001355937,0.00007220373,0.000006457972],"category_scores_gemma":[0.00007600288,0.00006247234,0.00002603699,0.000174119,0.0001352812,0.000002414026,0.000282384,0.00004029571,3.3682e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007125894,"about_ca_system_score_gemma":0.00002670426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005726492,"about_ca_topic_score_gemma":0.001244152,"domain_scores_codex":[0.9994571,0.0001000897,0.0001077781,0.0001511865,0.0000723516,0.0001114531],"domain_scores_gemma":[0.9996276,0.00001847723,0.00006928638,0.0001645164,0.000100141,0.00001992945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006826274,0.000003769156,0.9834121,0.00001096054,0.00004229619,4.249968e-7,0.00004605517,0.0005671232,0.002051116,0.00002307214,0.01319178,0.0005830232],"study_design_scores_gemma":[0.0003078597,0.00001531353,0.99542,0.000006768579,0.00001441377,0.00000146199,0.0000254994,0.0001241916,0.0003234974,0.00005456083,0.003648182,0.00005825626],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925806,0.0001022943,0.003929166,0.002938935,0.0001152052,0.0001811811,0.0001050246,0.000005296801,0.00004228924],"genre_scores_gemma":[0.9930319,0.00001298498,0.0003437278,0.006421953,0.00002181008,0.000002614046,0.0001062084,0.000001741607,0.00005702522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01200788,"threshold_uncertainty_score":0.2547548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0177441481964897,"score_gpt":0.2370645737759093,"score_spread":0.2193204255794196,"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."}}