{"id":"W2508552079","doi":"10.1111/faf.12177","title":"Transform high seas management to build climate resilience in marine seafood supply","year":2016,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Climate change; Exclusive economic zone; Fishery; Fishing; Sustainability; International waters; Fish stock; Fisheries management; Resilience (materials science); Psychological resilience; Geography; Environmental science; Environmental resource management; Business; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005626056,0.0003013228,0.0001956491,0.0003534587,0.0003327131,0.001343324,0.000447254,0.0004887466,0.004969917],"category_scores_gemma":[0.001225026,0.0001360465,0.000623563,0.0004073509,0.0007289731,0.001314443,0.001426019,0.0003849882,0.000288993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001283506,"about_ca_system_score_gemma":0.001286024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01271287,"about_ca_topic_score_gemma":0.01347904,"domain_scores_codex":[0.9997957,0.00009313691,0.000008501447,0.00002942083,0.00001824911,0.0000550465],"domain_scores_gemma":[0.9995558,0.00006262496,0.0001510659,0.00005216358,0.00006595636,0.0001123492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002041465,0.0004004351,0.1709536,0.0001537717,0.0003972352,0.0005880835,0.0002724539,0.7311198,0.007561934,0.05227847,0.00303793,0.0330322],"study_design_scores_gemma":[0.00008980138,0.0007563704,0.1685799,0.0001573105,0.000295998,0.0002142453,0.003004867,0.7072766,0.004821223,0.1002347,0.01448541,0.0000835524],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9582485,0.0001570588,0.01995159,0.002510627,0.00004745121,0.00004025672,0.0002721722,0.0001270193,0.01864529],"genre_scores_gemma":[0.9981915,0.00007367098,0.001165641,0.00005487563,0.000004442314,0.000006167448,0.0000341656,0.000005344999,0.0004641773],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01271287,"threshold_uncertainty_score":0.02527773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006206149980076718,"score_gpt":0.2076498873745258,"score_spread":0.2014437373944491,"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."}}