{"id":"W2116978523","doi":"10.1111/jbi.12404","title":"The influence of biogeographical barriers on the population genetic structure and gene flow in a coastal Pacific seabird","year":2014,"lang":"en","type":"article","venue":"Journal of Biogeography","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Environment Canada","keywords":"Gene flow; Subspecies; Population; Coalescent theory; Genetic structure; Range (aeronautics); Geography; Ecology; Biology; Genetic variation; Zoology; Gene; Genetics; Demography","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":[0.0003225687,0.0001408621,0.0001596959,0.0004714848,0.000385898,0.0005612976,0.0001534961,0.0001280542,0.0006454988],"category_scores_gemma":[0.001211932,0.0001045092,0.0001170458,0.0002753403,0.0005215987,0.0002422518,0.0003837761,0.0002212583,0.0000402277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002989595,"about_ca_system_score_gemma":0.0002965545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02091408,"about_ca_topic_score_gemma":0.04260396,"domain_scores_codex":[0.9998201,0.0000562092,0.00001244606,0.00005169653,0.00003377413,0.00002594373],"domain_scores_gemma":[0.9991952,0.0002706653,0.0002750742,0.00004454516,0.00008868532,0.00012584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008800085,0.00001562185,0.9909218,0.0000119964,0.00006724276,0.0000657332,0.0004342574,0.0002666051,0.004592573,0.00005836349,0.00002682508,0.003451017],"study_design_scores_gemma":[0.000001422981,0.00001557114,0.9994403,0.000002736149,0.000009148058,0.00001933315,0.0001890911,0.0001879601,0.00007703801,0.00001567781,0.00004065976,0.000001219455],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998332,0.00001774868,0.00002551377,0.000004592906,2.775303e-7,4.718788e-7,0.000008197031,4.642123e-7,0.0001094805],"genre_scores_gemma":[0.9998778,0.00001741947,0.00005362535,0.000003899514,0.000001068708,0.000001226501,0.00001763445,5.194826e-7,0.00002669051],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02091408,"threshold_uncertainty_score":0.04158467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003196300463118567,"score_gpt":0.1911529393920288,"score_spread":0.1879566389289102,"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."}}