{"id":"W4308388870","doi":"10.1016/j.gecco.2022.e02327","title":"Nested population structure of threatened boreal caribou revealed by network analysis","year":2022,"lang":"en","type":"article","venue":"Global Ecology and Conservation","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"West Fraser (Canada); University of Saskatchewan; Alberta Environment and Protected Areas; University of Guelph; Alberta Pacific Forest Industries; Weyerhauser (Canada)","funders":"Forest Resource Improvement Association of Alberta","keywords":"Woodland caribou; Threatened species; Geography; Population; Range (aeronautics); Boreal; Ecology; Vital rates; Landscape connectivity; Biological dispersal; Biology; Habitat; Population growth; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002058488,0.00009795272,0.0002123559,0.00002590826,0.0003917603,0.000006032794,0.0001004249,0.0001188344,0.0009477294],"category_scores_gemma":[0.00003027134,0.0001060649,0.00004346312,0.0008710237,0.000110229,0.0001183345,0.0001181367,0.00009639181,0.000002363206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001542859,"about_ca_system_score_gemma":0.00001855656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005258681,"about_ca_topic_score_gemma":0.01493588,"domain_scores_codex":[0.9989285,0.0002515043,0.0002667721,0.0002490072,0.0001265034,0.0001776551],"domain_scores_gemma":[0.9995242,0.00006271472,0.0002283528,0.0001316432,0.0000160842,0.00003698924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009978071,0.00002800225,0.9832918,0.000002284293,0.00009847821,0.000001276633,0.00002960313,0.007021192,0.00007226873,0.001159128,0.007755633,0.0004405534],"study_design_scores_gemma":[0.000320993,0.00009111071,0.9886129,5.717516e-7,0.0002278386,0.00000740201,0.00003543752,0.003759254,0.000004033014,0.00643006,0.000417969,0.00009240881],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973984,0.00003759557,0.0001026779,0.001700747,0.0001274446,0.0001866479,0.0001513864,0.00002369551,0.0002713627],"genre_scores_gemma":[0.9962921,0.000005661275,0.0002075712,0.002187252,0.00001290962,0.00002145625,0.001202866,0.000003000134,0.00006724612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0096772,"threshold_uncertainty_score":0.9999655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004039959889087824,"score_gpt":0.2010304365933772,"score_spread":0.1969904767042894,"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."}}