{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001173792,0.00008614327,0.0001029906,0.00006127035,0.00118811,0.000009044642,0.00006713899,0.0001696195,0.00003508608],"category_scores_gemma":[0.00006348972,0.00009510796,0.00002766116,0.00007321894,0.0002620675,0.000008847111,0.000533492,0.00006791734,0.000003954734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002971583,"about_ca_system_score_gemma":0.00001699973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004814448,"about_ca_topic_score_gemma":0.0006902001,"domain_scores_codex":[0.9993734,0.00008487982,0.0001158648,0.0002155277,0.00007553979,0.000134765],"domain_scores_gemma":[0.9996686,0.00001307548,0.00008714179,0.0001066326,0.00007183496,0.00005270971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005182302,0.00000982966,0.9926385,0.00001235358,0.00002991414,8.310876e-7,0.0003435436,0.00006708011,0.003824201,0.001832913,0.001170363,0.0000186335],"study_design_scores_gemma":[0.0003356397,0.0001841832,0.9931282,0.000005813282,0.00005055642,0.00001444045,0.001124343,0.00005973267,0.0004425524,0.004040903,0.0005146214,0.00009894698],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937657,0.0001838891,0.00487684,0.0002242784,0.0002144637,0.00007485901,0.00002287309,0.000007334134,0.0006297457],"genre_scores_gemma":[0.9980525,0.0001130249,0.0009558729,0.00004306868,0.0001542155,5.711058e-7,0.00002321644,0.000003163555,0.0006543538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004286796,"threshold_uncertainty_score":0.9138104,"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."}}