{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008586519,0.0005782284,0.0002263586,0.000565708,0.0003150041,0.000953727,0.0003866802,0.0005740993,0.003029073],"category_scores_gemma":[0.001941919,0.0001174429,0.0006939169,0.001245601,0.0003347825,0.001569501,0.0007887569,0.0004948572,0.0004985428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001098221,"about_ca_system_score_gemma":0.0007038547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01293447,"about_ca_topic_score_gemma":0.01264303,"domain_scores_codex":[0.9997262,0.00006691673,0.00001627612,0.00004157205,0.0000616835,0.00008725705],"domain_scores_gemma":[0.9992834,0.0001313718,0.0001886031,0.00003240839,0.00027402,0.0000903199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007855952,0.000206087,0.525493,0.000457682,0.0005348972,0.001820467,0.0003367634,0.3422633,0.01068142,0.02591981,0.01726471,0.07423623],"study_design_scores_gemma":[0.00007715639,0.0004368236,0.680514,0.0002093032,0.0005057711,0.00124543,0.003066822,0.2431763,0.008346641,0.02942,0.03277857,0.00022326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.965029,0.0009552274,0.008279795,0.002625606,0.0001689687,0.0000255018,0.006219617,0.0001822828,0.01651393],"genre_scores_gemma":[0.994456,0.0006780594,0.001528042,0.0001939868,0.00002177291,0.00002294747,0.001952688,0.00002399369,0.001122545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01293447,"threshold_uncertainty_score":0.02571839,"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."}}