{"id":"W3200510275","doi":"10.1016/j.oneear.2021.08.009","title":"Interventions for improving the productivity and environmental performance of global aquaculture for future food security","year":2021,"lang":"en","type":"article","venue":"One Earth","topic":"Aquaculture Nutrition and Growth","field":"Agricultural and Biological Sciences","cited_by":157,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia; University of Waterloo","funders":"Kjell och Märta Beijers Stiftelse; Consortium of International Agricultural Research Centers; Svenska Forskningsrådet Formas","keywords":"Food security; Productivity; Aquaculture; Business; Natural resource economics; Sustainability; Psychological intervention; Food systems; Environmental resource management; Environmental economics; Fish <Actinopterygii>; Fishery; Economics; Economic growth; Ecology; Biology; Agriculture; Medicine","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":[0.003114933,0.0005415711,0.0001887595,0.0007601011,0.000665001,0.001262215,0.0008176476,0.000961943,0.01340026],"category_scores_gemma":[0.004082052,0.00008829038,0.0005048051,0.0004333206,0.001045552,0.001014299,0.003199297,0.0009436219,0.0006455702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009467008,"about_ca_system_score_gemma":0.004624987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001721501,"about_ca_topic_score_gemma":0.005454591,"domain_scores_codex":[0.9985313,0.0009159092,0.00005398335,0.0001026954,0.0001854805,0.0002105739],"domain_scores_gemma":[0.9984311,0.0005124322,0.0005211292,0.0001437603,0.0001792227,0.0002122892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004761859,0.002996938,0.01815003,0.004776828,0.0003434354,0.0002262234,0.001027918,0.004634015,0.0217222,0.04185209,0.01758553,0.8862086],"study_design_scores_gemma":[0.0008644174,0.009187326,0.1976263,0.01782333,0.001183407,0.0005427052,0.009269136,0.003937313,0.02731072,0.1095898,0.6224785,0.0001868972],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4219298,0.05525342,0.07878395,0.1655632,0.002653152,0.002313863,0.001761674,0.001834602,0.2699063],"genre_scores_gemma":[0.8740737,0.03371258,0.06635506,0.01217677,0.0005319881,0.001526082,0.0005065597,0.00007776737,0.01103947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01340026,"threshold_uncertainty_score":0.0448283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01609038857696916,"score_gpt":0.2159997212319965,"score_spread":0.1999093326550274,"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."}}