{"id":"W3176584963","doi":"10.1371/journal.pone.0253895","title":"Assessing recovery of spectacled eiders using a Bayesian decision analysis","year":2021,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Bureau of Land Management; Auburn University; Ducks Unlimited Canada","keywords":"Threatened species; Endangered species; Population; IUCN Red List; Near-threatened species; Abundance (ecology); Extinction (optical mineralogy); Ecology; Fishery; Environmental resource management; Biology; Environmental science; Demography; Habitat","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0113095,0.000654435,0.0009675872,0.001830639,0.0007418201,0.001446013,0.0015016,0.001312313,0.002301553],"category_scores_gemma":[0.02257672,0.0006045076,0.001441453,0.0008752534,0.0009596879,0.001574836,0.001138957,0.001379475,0.0002413494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002364716,"about_ca_system_score_gemma":0.001805197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02913492,"about_ca_topic_score_gemma":0.02399485,"domain_scores_codex":[0.9969061,0.001721244,0.0001984665,0.0005655947,0.0003543794,0.0002541846],"domain_scores_gemma":[0.9870307,0.01002767,0.001342795,0.0003352423,0.0009408575,0.0003228315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002394565,0.00009474181,0.04235194,0.0000661581,0.0001814571,0.0001223332,0.0002623735,0.9166173,0.0005359576,0.01173071,0.0006748116,0.02712262],"study_design_scores_gemma":[0.0000167776,0.0000608191,0.006660506,0.00002760896,0.0000385522,0.00002703215,0.00005515737,0.9840333,0.0001780682,0.008590449,0.0002868373,0.00002486038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6153633,0.0002937739,0.3781474,0.001062532,0.00002794621,0.0002495098,0.0006462381,0.0001848134,0.004024541],"genre_scores_gemma":[0.9387832,0.0001334944,0.059151,0.0001092181,0.0000209166,0.0001596028,0.000467876,0.00001418464,0.001160413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02913492,"threshold_uncertainty_score":0.05981112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05460218678715577,"score_gpt":0.2556772988413188,"score_spread":0.2010751120541631,"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."}}