{"id":"W2153905523","doi":"10.1111/j.1365-2486.2009.01995.x","title":"Large‐scale redistribution of maximum fisheries catch potential in the global ocean under climate change","year":2009,"lang":"en","type":"article","venue":"Global Change Biology","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":1194,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Oceanic and Atmospheric Administration; University of British Columbia; Pew Charitable Trusts","keywords":"Climate change; Exclusive economic zone; Fishing; Geography; Fishery; Oceanography; Tropics; Biome; Environmental science; Ecology; Ecosystem; Geology; 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":[0.0004174445,0.0002234164,0.0001825376,0.0006536922,0.0002088819,0.0005465017,0.000187602,0.0002555969,0.001190103],"category_scores_gemma":[0.0005683437,0.00009257046,0.0005040591,0.0009644883,0.0002434732,0.0005102336,0.0005839001,0.0002060316,0.0001154139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005122462,"about_ca_system_score_gemma":0.0002507436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01107566,"about_ca_topic_score_gemma":0.008700569,"domain_scores_codex":[0.9998845,0.00002464477,0.000008900312,0.00003319084,0.00001793953,0.00003077149],"domain_scores_gemma":[0.9997301,0.00003959681,0.0001080518,0.00002921313,0.00005636468,0.00003671191],"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":[0.0002078522,0.00005847875,0.9549632,0.00005614088,0.0003832426,0.0002806541,0.0001097865,0.0265091,0.005654118,0.0005474454,0.0009953183,0.01023476],"study_design_scores_gemma":[0.000005233702,0.00003779859,0.9888694,0.000007978952,0.00003777427,0.00004096785,0.0002168214,0.009547474,0.0004644292,0.000232591,0.0005291226,0.00001036073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979157,0.00008339303,0.0003175539,0.0000951918,0.00000612805,0.000003222223,0.0007144299,0.00001463237,0.0008497199],"genre_scores_gemma":[0.9993228,0.0000483062,0.0001114988,0.00001983841,0.000002593457,0.000003278444,0.0004065425,0.00000212544,0.00008300864],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01107566,"threshold_uncertainty_score":0.02202237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03029378529509531,"score_gpt":0.2849274981527738,"score_spread":0.2546337128576785,"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."}}