{"id":"W4416894625","doi":"10.1111/1365-2664.70213","title":"Local knowledge enhances the sustainability of interconnected fisheries","year":2025,"lang":"en","type":"article","venue":"Journal of Applied Ecology","topic":"Fish biology, ecology, and behavior","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Conservation Fund of Canada; Fundação de Amparo à Pesquisa do Estado do Amazonas; Mulago Foundation; Rolex; National Geographic Society; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Israel Science Foundation; Fundação para a Ciência e a Tecnologia; Gordon and Betty Moore Foundation","keywords":"Metapopulation; Fishing; Population; Sustainability; Biodiversity; Fisheries management; Abundance (ecology); Indigenous","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001564157,0.000363334,0.0003719447,0.001119717,0.001107677,0.002278679,0.0008369759,0.0008968056,0.005332653],"category_scores_gemma":[0.007593085,0.0002051316,0.0004974795,0.0008249261,0.002139773,0.004084063,0.003709073,0.0003940492,0.0002068707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001657955,"about_ca_system_score_gemma":0.001082339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005822943,"about_ca_topic_score_gemma":0.008073631,"domain_scores_codex":[0.9992354,0.0002421711,0.00003962107,0.0002216105,0.0000897827,0.0001713648],"domain_scores_gemma":[0.996129,0.001552487,0.001175722,0.0005202413,0.0002966017,0.0003259124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003715628,0.0004920746,0.262716,0.001003147,0.0006536472,0.002110307,0.00615839,0.3551659,0.008510971,0.1742017,0.002014376,0.186602],"study_design_scores_gemma":[0.0001163645,0.0008294247,0.2161914,0.0005084567,0.0005352611,0.000797704,0.01147926,0.3480487,0.003549377,0.4006935,0.0171196,0.0001311085],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9503938,0.0003092766,0.01722934,0.0007652441,0.000008737814,0.00005105696,0.000121696,0.00005694832,0.03106383],"genre_scores_gemma":[0.9988651,0.00004249101,0.0008186994,0.00001575992,0.000001968641,0.000005960807,0.00001335838,0.000002910151,0.0002336448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005822943,"threshold_uncertainty_score":0.01783949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007134458853886479,"score_gpt":0.2517750003942481,"score_spread":0.2446405415403616,"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."}}