{"id":"W4415714869","doi":"10.1016/j.fishres.2025.107571","title":"Integrating a seabird diet-derived recruitment index into a stock assessment model of Atlantic herring in the Northeast U.S.","year":2025,"lang":"en","type":"article","venue":"Fisheries Research","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Herring; Clupea; Atlantic herring; Seabird; Stock assessment; Provisioning; Abundance (ecology)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008948126,0.0004371925,0.0002543778,0.000413026,0.0003252206,0.0009205688,0.0006351749,0.0005118413,0.0007254235],"category_scores_gemma":[0.001533617,0.0004337069,0.000448811,0.0002232237,0.0002815317,0.0005711439,0.0004943869,0.0004481539,0.0001365022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001527508,"about_ca_system_score_gemma":0.001098181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1461293,"about_ca_topic_score_gemma":0.1704336,"domain_scores_codex":[0.9998372,0.00004970782,0.00001153048,0.00006168681,0.00001360848,0.00002630335],"domain_scores_gemma":[0.9995747,0.0001744362,0.0001074847,0.00001617365,0.00007551483,0.00005158457],"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":[0.00003926906,0.00006025056,0.09876567,0.00001219939,0.00008562809,0.00009667576,0.00009423025,0.8946831,0.0006667429,0.0005838844,0.0001429346,0.004769461],"study_design_scores_gemma":[0.000002874853,0.00001753133,0.008916266,0.000003525052,0.00001459986,0.000009308602,0.00002918081,0.9906988,0.0000501266,0.0001990723,0.00005464363,0.000004151515],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908875,0.00006294572,0.008049583,0.0001230793,0.000004709758,0.00001172808,0.0001471069,0.0000314266,0.0006819189],"genre_scores_gemma":[0.9975035,0.00002878827,0.001805642,0.0000179248,0.000002246871,0.000009737212,0.0001163715,0.000003686079,0.0005121495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1461293,"threshold_uncertainty_score":0.2905575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1116303026009426,"score_gpt":0.3825485825606704,"score_spread":0.2709182799597278,"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."}}