{"id":"W4212946307","doi":"10.1111/faf.12649","title":"Managing fisheries for maximum nutrient yield","year":2022,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Aquaculture Nutrition and Growth","field":"Agricultural and Biological Sciences","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"H2020 European Research Council; Australian Research Council; Royal Society; Leverhulme Trust","keywords":"Fishery; Fishing; Nutrient; Nutrient management; Fisheries management; Food security; Maximum sustainable yield; Overfishing; Business; Environmental science; Biology; Ecology; Agriculture","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":[0.00326325,0.0006234168,0.0003486014,0.001160776,0.001145347,0.002539799,0.001947168,0.00104702,0.001838833],"category_scores_gemma":[0.004042038,0.0002447895,0.000490947,0.0007829141,0.001223182,0.003934841,0.003856235,0.0006971526,0.0002059787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002959536,"about_ca_system_score_gemma":0.00500964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008543943,"about_ca_topic_score_gemma":0.01519003,"domain_scores_codex":[0.9989755,0.0002910464,0.00007137013,0.0002390346,0.0002728676,0.000150219],"domain_scores_gemma":[0.9986231,0.0001771377,0.0005485365,0.0001252728,0.0003022533,0.0002236529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007088097,0.0002146392,0.04936391,0.0004743241,0.0002584377,0.0005249448,0.00120918,0.3473244,0.0100525,0.3720259,0.01056959,0.2079114],"study_design_scores_gemma":[0.00005407106,0.0005643502,0.04171585,0.0008024179,0.0001544916,0.0004224805,0.004377326,0.3552443,0.005622659,0.4904098,0.1004196,0.0002125852],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2424555,0.001771498,0.6733685,0.01678674,0.0002361414,0.0004809161,0.0004705522,0.0006314057,0.06379883],"genre_scores_gemma":[0.9143677,0.0008831647,0.0814307,0.0003597283,0.00004860325,0.0001997212,0.00009846436,0.0000334713,0.002578435],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008543943,"threshold_uncertainty_score":0.02147305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02449238481340445,"score_gpt":0.1969170113397803,"score_spread":0.1724246265263758,"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."}}