{"id":"W2903981006","doi":"10.1002/ece3.4530","title":"Partitioning genetic and species diversity refines our understanding of species–genetic diversity relationships","year":2018,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Fondo Nacional de Desarrollo Científico y Tecnológico; Comisión Nacional de Investigación Científica y Tecnológica; Universidad El Bosque","keywords":"Biology; Genetic diversity; Species richness; Evolutionary biology; Species evenness; Conservation genetics; Genetic variation; Ecology; Genetics; Population; Allele; Microsatellite; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002786302,0.0005299505,0.00079124,0.002870589,0.0006751798,0.001455645,0.0003685357,0.0004758215,0.0014551],"category_scores_gemma":[0.004961306,0.0003476718,0.0008154631,0.002002314,0.001101516,0.001428221,0.001320771,0.001050388,0.0002184428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004895598,"about_ca_system_score_gemma":0.0004500498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004528956,"about_ca_topic_score_gemma":0.009058277,"domain_scores_codex":[0.9985482,0.0005185196,0.00009025793,0.0006367632,0.0001165074,0.00008972165],"domain_scores_gemma":[0.9949994,0.003077296,0.0006170121,0.0008231046,0.0002727407,0.0002104552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003245393,0.0001391661,0.8108736,0.0004853025,0.002459752,0.0002847966,0.001742792,0.01455922,0.1108602,0.00487201,0.0005479383,0.0528507],"study_design_scores_gemma":[0.00001641552,0.00007136645,0.9446138,0.0000597138,0.0002047689,0.0001772529,0.000698589,0.03986925,0.002648517,0.009140809,0.002446434,0.00005316934],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9752319,0.0008056604,0.02131565,0.0001118969,0.000009382733,0.00001919787,0.0006657337,0.00009514185,0.001745313],"genre_scores_gemma":[0.9919422,0.0001279402,0.007386702,0.00006002397,0.00001039207,0.000009103087,0.0003470838,0.00001948035,0.00009708155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004528956,"threshold_uncertainty_score":0.01473558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05127426680243545,"score_gpt":0.227686930269184,"score_spread":0.1764126634667486,"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."}}