{"id":"W4410290537","doi":"10.1002/eap.70036","title":"Evaluating ecosystem caps on fishery yield in the context of climate stress and predation","year":2025,"lang":"en","type":"article","venue":"Ecological Applications","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Fisheries and Oceans Canada","funders":"North Pacific Research Board; Cooperative Institute for Climate, Ocean, and Ecosystem Studies, University of Washington","keywords":"Groundfish; Ecosystem; Fishing; Fisheries management; Fishery; Context (archaeology); Marine ecosystem; Ecosystem services; Predation; Environmental science; Maximum sustainable yield; Overexploitation; Ecology; Geography; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004081148,0.00004227501,0.00007102016,0.00001699143,0.00009523831,0.0000170514,0.000160537,0.00004214402,0.0009853264],"category_scores_gemma":[0.0001049079,0.00002764719,0.0000135063,0.0001969546,0.00006609871,0.0000340294,0.0001371866,0.00009748426,0.00002226418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003589261,"about_ca_system_score_gemma":0.000005149998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007607097,"about_ca_topic_score_gemma":0.001037132,"domain_scores_codex":[0.9994019,0.00007427048,0.0001541685,0.0001517245,0.000112582,0.0001053938],"domain_scores_gemma":[0.9993159,0.0004689994,0.00003671136,0.0001571953,0.000006467093,0.00001470268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002992939,0.0004778911,0.7979156,0.00006902716,0.00000630278,7.781733e-7,0.0002881098,0.0002210442,0.0006036008,0.0188539,0.0006962661,0.1808375],"study_design_scores_gemma":[0.0001765653,0.0001774663,0.9820989,0.00001386938,0.000006343338,5.262688e-7,0.001010126,0.004062525,0.0003043435,0.001935674,0.01014763,0.00006597666],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7634375,0.000002933255,0.00007690712,0.001069613,0.000007120885,0.0006538653,0.0000169028,0.000007608502,0.2347275],"genre_scores_gemma":[0.9988438,0.00003389846,0.0001021719,0.0002610041,0.000006016639,0.0005965794,0.000008428517,0.000001240697,0.0001468344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2354063,"threshold_uncertainty_score":0.9999279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04247657797967194,"score_gpt":0.325042913083561,"score_spread":0.2825663351038891,"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."}}