{"id":"W2024032905","doi":"10.1016/j.biocon.2013.12.040","title":"Revisiting Western Hudson Bay: Using aerial surveys to update polar bear abundance in a sentinel population","year":2014,"lang":"en","type":"article","venue":"Biological Conservation","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":92,"is_retracted":false,"has_abstract":false,"ca_institutions":"Government of Nunavut","funders":"","keywords":"Transect; Aerial survey; Abundance (ecology); Bay; Distance sampling; Population; Geography; Shore; Mark and recapture; Physical geography; Sampling (signal processing); Abundance estimation; Habitat; Ecology; Environmental science; Fishery; Oceanography; Cartography; Demography; Geology; Archaeology; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00132443,0.0001221874,0.0001938621,0.00002144152,0.0001103086,0.00003230802,0.0001167431,0.00007485846,0.0002931777],"category_scores_gemma":[0.0004632495,0.0001059108,0.00003198859,0.0002434929,0.00003526995,0.0001399356,0.0002636716,0.00007614959,0.0001605167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001116324,"about_ca_system_score_gemma":0.000002082039,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009212561,"about_ca_topic_score_gemma":0.003080916,"domain_scores_codex":[0.9986055,0.0003941572,0.0003040933,0.0003333722,0.0001389977,0.0002238938],"domain_scores_gemma":[0.9996164,0.00007454807,0.0001178666,0.0001265779,0.00001240416,0.00005217742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001658544,0.00001034878,0.9895124,0.000005791242,0.000001424584,8.136583e-7,0.00001073216,0.00009114857,0.003221536,0.0002216731,0.00001349204,0.006894023],"study_design_scores_gemma":[0.0001567697,0.00003455094,0.9912654,0.00002774776,0.000002736599,0.000001149097,0.000004086068,0.003092424,0.00003148843,0.000191299,0.005052956,0.0001394623],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958795,0.0000167654,0.002484699,0.0009704805,0.00005214251,0.0002156542,0.00000318956,0.0000359116,0.0003417151],"genre_scores_gemma":[0.9958888,0.00001657667,0.002271161,0.001659227,0.0001050424,0.000006751301,0.00003248959,0.000006900786,0.00001309796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00675456,"threshold_uncertainty_score":0.9973852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.062916920950096,"score_gpt":0.2849683692265922,"score_spread":0.2220514482764962,"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."}}