{"id":"W2143174897","doi":"10.1890/13-0388.1","title":"Landscape context affects genetic diversity at a much larger spatial extent than population abundance","year":2014,"lang":"en","type":"article","venue":"Ecology","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Abundance (ecology); Ecology; Diversity (politics); Geography; Context (archaeology); Genetic diversity; Population; Biology; Sociology; Demography; Anthropology","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":[0.0001022952,0.0001330402,0.0001540965,0.00003722726,0.0003213645,0.00001193221,0.000162808,0.0002243156,0.0003767312],"category_scores_gemma":[0.00005001415,0.0001359895,0.00007878446,0.00004134069,0.00004642848,0.000002997644,0.000414352,0.00006407951,0.00008332582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002104431,"about_ca_system_score_gemma":0.00001239979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001796088,"about_ca_topic_score_gemma":0.004740248,"domain_scores_codex":[0.9990748,0.0001335224,0.0001096487,0.000335261,0.0001090512,0.0002377336],"domain_scores_gemma":[0.9995138,0.00001735776,0.00009535489,0.0002462569,0.00004337867,0.00008385035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008772408,0.00002413806,0.989897,0.000009672869,0.0000293474,0.00000266722,0.00009063454,0.000303794,0.003991226,0.00008948975,0.003626694,0.001847589],"study_design_scores_gemma":[0.0007648778,0.0002310682,0.9818565,0.000002207999,0.00002495868,0.00001578914,0.00002319855,0.0003088446,0.001664135,0.0001697836,0.01477827,0.000160321],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972753,0.000108675,0.0009964602,0.0001669441,0.0006187946,0.0001609781,0.00001851325,0.00001587014,0.0006384887],"genre_scores_gemma":[0.9974039,0.0000186642,0.0002523705,0.0005791553,0.0002725752,0.000004443953,0.000256145,0.000009700917,0.001203049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01115157,"threshold_uncertainty_score":0.554549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006242783399920822,"score_gpt":0.2033661683532055,"score_spread":0.1971233849532847,"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."}}