{"id":"W4392761135","doi":"10.1002/jwmg.22573","title":"Canadian murre harvest management in the face of uncertainty: a potential biological removal approach","year":2024,"lang":"en","type":"article","venue":"Journal of Wildlife Management","topic":"Avian ecology and behavior","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Environment and Climate Change Canada","keywords":"Bycatch; Wildlife; Uria aalge; Fishery; Population; Geography; Sustainability; Fisheries management; Wildlife management; Ecology; Biology; Fishing; Seabird; Predation; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001766722,0.0005086964,0.0004993915,0.0009561103,0.001712042,0.001514538,0.00254262,0.00086784,0.003123987],"category_scores_gemma":[0.00478331,0.0002608339,0.0007021972,0.0007029829,0.0009722197,0.0006984873,0.00106541,0.001011478,0.0001394349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01034789,"about_ca_system_score_gemma":0.008944432,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7146106,"about_ca_topic_score_gemma":0.8037221,"domain_scores_codex":[0.9992985,0.000200557,0.00001906638,0.00009771078,0.0001680686,0.0002161756],"domain_scores_gemma":[0.9981202,0.0006510789,0.0002392051,0.00009948794,0.0006619856,0.0002280011],"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":[0.00009817504,0.00004516915,0.01534109,0.00004111635,0.00007522095,0.0001431021,0.0001167382,0.9677899,0.0003481304,0.005114045,0.001173829,0.009713617],"study_design_scores_gemma":[0.00003656127,0.0001463356,0.01244351,0.00003608311,0.0001145873,0.00005769344,0.0004720885,0.979607,0.0002454197,0.003202928,0.003585711,0.00005197901],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9037505,0.0005568203,0.04105365,0.002273005,0.00009893284,0.0002646858,0.0009980492,0.0001639298,0.05084039],"genre_scores_gemma":[0.990625,0.0001212243,0.006545945,0.0001250444,0.000007433967,0.00004253455,0.000170326,0.00001221816,0.00235031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2853894,"threshold_uncertainty_score":0.5741403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0172416260434398,"score_gpt":0.2404726987540606,"score_spread":0.2232310727106208,"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."}}