{"id":"W2512978457","doi":"10.1038/srep32607","title":"Projected change in global fisheries revenues under climate change","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":288,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Fisheries and Oceans Canada","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Wellcome Trust; Paul G. Allen Family Foundation","keywords":"Climate change; Fishing; Fishery; Fisheries management; Sustainability; Revenue; Fish stock; Natural resource economics; Business; Environmental science; Geography; Ecology; Economics; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000930323,0.0001259391,0.0001416507,0.00005285885,0.0001639912,0.0001385404,0.0001926799,0.00006682677,0.005830294],"category_scores_gemma":[0.0000985473,0.00008653852,0.00004451094,0.000820374,0.0005194094,0.0007247341,0.0005253756,0.00006397214,0.0002165165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002371193,"about_ca_system_score_gemma":0.00001929837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001631757,"about_ca_topic_score_gemma":0.004008357,"domain_scores_codex":[0.9977997,0.00006279243,0.0002923019,0.0006820947,0.0005824038,0.0005807219],"domain_scores_gemma":[0.9991279,0.00001453324,0.0001089745,0.0006174232,0.00001873424,0.0001123991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000109272,0.00004587345,0.898139,0.000009875675,0.000001655111,0.0002472616,0.0002974123,6.836488e-8,0.001115744,0.00004016277,0.00538142,0.09471061],"study_design_scores_gemma":[0.0001653173,0.00004353831,0.7041863,0.00004183151,0.000003034801,0.00008678486,0.00006495578,0.00001902655,0.0004439954,0.005332181,0.2893822,0.0002307793],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8981258,0.00002914748,0.00001078603,0.002828418,0.002193649,0.0008502379,0.00001673397,0.00008710098,0.09585809],"genre_scores_gemma":[0.9937729,0.00005622006,0.0001404767,0.0001478706,0.000108843,0.0002744059,0.00001523146,0.00001272881,0.005471385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2840008,"threshold_uncertainty_score":0.9950785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04956111672023625,"score_gpt":0.2910290780803182,"score_spread":0.2414679613600819,"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."}}