{"id":"W2545301885","doi":"10.1002/ece3.2563","title":"Assessing polar bear (<i>Ursus maritimus</i>) population structure in the Hudson Bay region using <scp>SNP</scp>s","year":2016,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University; Ministry of Natural Resources and Forestry; Environment and Climate Change Canada; University of New Brunswick; Government of Nunavut; Alberta Environment and Protected Areas; University of Alberta","funders":"Aboriginal Affairs and Northern Development Canada; Environment Canada; Natural Sciences and Engineering Research Council of Canada; Directorate for Biological Sciences; Alberta Innovates; Churchill Northern Studies Centre; University of Alberta; Parks Canada; World Wildlife Fund","keywords":"Bay; Ursus maritimus; Population; Geography; Microsatellite; Ecology; Genetic structure; Population genetics; Biology; Zoology; Arctic; Archaeology; Genetic variation; Genetics; Demography; Allele","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":[0.0002900064,0.0001074879,0.0001237399,0.00003282158,0.0003147371,0.00002514041,0.00009987403,0.0001323494,0.00009165597],"category_scores_gemma":[0.0001469064,0.00007021116,0.00002383143,0.0001644322,0.0001189837,0.0004737575,0.0001412349,0.0001208527,0.00001949952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003156146,"about_ca_system_score_gemma":0.000006096882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002223954,"about_ca_topic_score_gemma":0.01107477,"domain_scores_codex":[0.9990016,0.0002119877,0.0001597141,0.0002446073,0.0001196067,0.0002624626],"domain_scores_gemma":[0.9996057,0.0001479793,0.00009195456,0.0001200173,0.000005983498,0.00002834363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003979901,0.0000160473,0.9949521,0.0000067192,0.000003523753,0.00000590214,0.0001025067,0.00004004143,0.001166094,0.0004040054,0.0005244082,0.002774659],"study_design_scores_gemma":[0.0002474832,0.00004591054,0.9939233,0.00001699344,0.0000158178,0.00004764616,0.0001674901,0.0004530959,0.00001062099,0.00338277,0.001641133,0.0000477129],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974295,0.0001998652,0.000333058,0.0005038023,0.0001378101,0.0001666809,0.000002298061,0.00001548255,0.001211499],"genre_scores_gemma":[0.9991902,0.00006904067,0.0003579514,0.0002516414,0.00006629543,0.000004637768,0.000004703119,0.000006473166,0.00004910916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008850821,"threshold_uncertainty_score":0.6179984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02188789230488295,"score_gpt":0.2547461575725053,"score_spread":0.2328582652676224,"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."}}