{"id":"W2551900470","doi":"10.1111/eva.12443","title":"Environmental and anthropogenic drivers of connectivity patterns: A basis for prioritizing conservation efforts for threatened populations","year":2016,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Association of Petroleum Producers; Alberta Conservation Association; ConocoPhillips; Shell; Ministry of Forests, Lands and Natural Resource Operations; Parks Canada; World Wildlife Fund","keywords":"Threatened species; Biological dispersal; Landscape connectivity; Ecology; Habitat fragmentation; Biology; Habitat; Population; Habitat destruction; Gene flow; Resistance (ecology); Predation; Geography; Genetic variation; Demography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005247482,0.00007738985,0.00008084516,0.00003153792,0.000218884,0.00000379104,0.00005310529,0.00008022421,0.00001702474],"category_scores_gemma":[0.00002187917,0.00007243966,0.00006416507,0.00002785569,0.0001024174,0.000009919906,0.00003371733,0.00001238026,8.495606e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002107811,"about_ca_system_score_gemma":0.00002465505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001142044,"about_ca_topic_score_gemma":0.00002124078,"domain_scores_codex":[0.999475,0.00001410221,0.0001363183,0.0002228282,0.00005635562,0.00009542226],"domain_scores_gemma":[0.9996222,0.00004555656,0.00009179624,0.0001540619,0.00004972404,0.00003664333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000101353,0.0000768035,0.502281,0.00004651432,0.00007238812,4.409663e-8,0.00004936651,0.00004315951,0.4786281,0.009587913,0.0005989884,0.008514391],"study_design_scores_gemma":[0.0009215496,0.0001311986,0.9617884,0.00001310336,0.00006827364,0.000007056578,0.0001087169,0.0001266985,0.01265216,0.004229436,0.01979876,0.0001546103],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7595289,0.0001479482,0.2376601,0.0003945254,0.00003281357,0.0007193342,0.001500016,0.000007136963,0.000009245858],"genre_scores_gemma":[0.9891163,0.00009732073,0.009839409,0.00004313529,0.00006268201,0.0002453849,0.0005029312,0.000007886462,0.00008498772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4659759,"threshold_uncertainty_score":0.2954004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01643972503778279,"score_gpt":0.249322008576381,"score_spread":0.2328822835385982,"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."}}