{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004389748,0.00009605513,0.0001012679,0.0008881959,0.0002113424,0.0001945125,0.0001693484,0.0001354682,0.0007654126],"category_scores_gemma":[0.0007219934,0.00006719796,0.0001071606,0.0009706805,0.0002795538,0.0002444513,0.0003291561,0.0001743575,0.00009164663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002377253,"about_ca_system_score_gemma":0.0001657588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007887737,"about_ca_topic_score_gemma":0.01770355,"domain_scores_codex":[0.9998337,0.00005659299,0.00001210138,0.00004641346,0.00003189729,0.00001916645],"domain_scores_gemma":[0.9992965,0.0001252994,0.0003486741,0.00005727257,0.00006178779,0.0001103907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002193537,0.000009050576,0.9963582,0.000008327975,0.00002999297,0.0000213196,0.0001676203,0.00007649628,0.0005836569,0.00002849212,0.0000932371,0.002601631],"study_design_scores_gemma":[9.048279e-7,0.00001494903,0.9996278,0.000002457155,0.00000387034,0.0000344065,0.0001054928,0.00006356923,0.00003030551,0.00001164775,0.0001038421,7.806393e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993415,0.00004197819,0.00005677829,0.00001950798,7.395637e-7,0.000002721893,0.0003260023,0.000001604033,0.0002091722],"genre_scores_gemma":[0.9992524,0.00004466699,0.0001746533,0.00001247479,0.000002671891,0.000005649553,0.0004147712,7.837993e-7,0.00009201909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007887737,"threshold_uncertainty_score":0.01568365,"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."}}