{"id":"W4391838457","doi":"10.1111/mms.13107","title":"A demographic survey of the Davis Strait polar bear subpopulation using physical and genetic capture‐recapture‐recovery sampling","year":2024,"lang":"en","type":"article","venue":"Marine Mammal Science","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Government of Nunavut; University of Alberta","funders":"Nuclear Safety and Security Commission; Environment and Climate Change Canada; Mitacs; International Association for Bear Research and Management; Parks Canada; Ministère des Forêts, de la Faune et des Parcs; World Wildlife Fund; National Aeronautics and Space Administration; Pinngortitaleriffik; Nunavut Wildlife Management Board; Makivik","keywords":"Mark and recapture; Sampling (signal processing); Biology; Geography; Population; Demography; Computer science","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":[0.0006774401,0.0001830814,0.0001965317,0.00006299304,0.0003265312,0.0001327151,0.0004722746,0.00003994761,0.0002099637],"category_scores_gemma":[0.0001697117,0.0001309238,0.00007978885,0.001870459,0.0009097896,0.0003182382,0.001840408,0.000187646,0.00001057153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001282328,"about_ca_system_score_gemma":0.00004158994,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08033466,"about_ca_topic_score_gemma":0.02719831,"domain_scores_codex":[0.9980946,0.00008428317,0.0002338735,0.0005539442,0.0006503942,0.0003829465],"domain_scores_gemma":[0.9994215,0.00009510186,0.00008139151,0.0002772925,0.00002415893,0.0001006033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00000816686,0.00002402948,0.9552973,0.00003465048,0.000008556441,0.000003220127,0.0001093178,0.0009842439,0.008986649,0.0001077274,0.00001455743,0.03442156],"study_design_scores_gemma":[0.00005300223,0.00004009682,0.9814476,0.00002655524,0.0000280015,0.00002156416,0.00001163737,0.01720002,0.0001013076,0.0006295123,0.0002855432,0.0001551049],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977246,0.0002040168,0.0002081833,0.00007651735,0.000165698,0.0002270298,0.00001935822,0.00002705449,0.001347561],"genre_scores_gemma":[0.9982924,0.00003351504,0.001491823,0.00006273474,0.00003948474,0.000003207901,0.000002235628,0.0000136348,0.00006095271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05313636,"threshold_uncertainty_score":0.9905528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0289354144581422,"score_gpt":0.2628417306295119,"score_spread":0.2339063161713697,"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."}}