{"id":"W2132270486","doi":"10.1139/f05-110","title":"Incorporating predation interactions in a statistical catch-at-age model for a predator-prey system in the eastern Bering Sea","year":2005,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Predation; Stock assessment; Fishery; Gadus; Pollock; Population; Stock (firearms); Fisheries management; Predator; Bioeconomics; Statistical model; Context (archaeology); Apex predator; Population model; Gadidae; Ecology; Statistics; Biology; Atlantic cod; Geography; Fishing; Mathematics; Fish <Actinopterygii>; Demography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.002093092,0.0006786065,0.0007586928,0.0006592592,0.0005351334,0.001073195,0.001373589,0.0008960164,0.001037709],"category_scores_gemma":[0.003666515,0.0006284866,0.001178875,0.0004233543,0.0007103826,0.001369408,0.0007829141,0.0007469542,0.0002479392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001602092,"about_ca_system_score_gemma":0.001467375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04297703,"about_ca_topic_score_gemma":0.03662415,"domain_scores_codex":[0.9995049,0.000215276,0.00004041685,0.00009821431,0.00006008681,0.00008117008],"domain_scores_gemma":[0.9983448,0.0008707604,0.0003949761,0.0000483023,0.0002157463,0.0001253481],"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":[0.00004656015,0.00002986609,0.01223339,0.00001709838,0.00005930712,0.0001344195,0.00008917891,0.9787451,0.0005807403,0.005149352,0.0001670275,0.002748042],"study_design_scores_gemma":[0.000004884541,0.00002884388,0.001916328,0.000002832372,0.00001929883,0.00002750613,0.00001531852,0.9964061,0.00003857574,0.001457452,0.00007394315,0.00000891936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8981811,0.000273111,0.09831744,0.0004334886,0.0000372218,0.00003726037,0.0002468503,0.00008778064,0.002385774],"genre_scores_gemma":[0.9870148,0.0001776452,0.008998577,0.00005817752,0.00002181605,0.0000609544,0.0001242376,0.00002230665,0.003521511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04297703,"threshold_uncertainty_score":0.08545375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04377880474994528,"score_gpt":0.2738853912229543,"score_spread":0.230106586473009,"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."}}