{"id":"W3013884180","doi":"10.1016/j.marpol.2020.103954","title":"Climate change increases the risk of fisheries conflict","year":2020,"lang":"en","type":"article","venue":"Marine Policy","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":149,"is_retracted":false,"has_abstract":false,"ca_institutions":"Fisheries and Oceans Canada; University of British Columbia","funders":"","keywords":"Climate change; Fisheries management; Fishery; Fish stock; Fisheries law; Productivity; Fish <Actinopterygii>; Business; Fisheries science; Effects of global warming; Global warming; Natural resource economics; Environmental resource management; Fishing; Environmental science; Ecology; Economics; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001509171,0.00009979666,0.0001361577,0.0000176013,0.0001091599,0.00002686143,0.0003469562,0.00002925296,0.01372094],"category_scores_gemma":[0.0003436375,0.00006609268,0.00005893594,0.0003614232,0.0003219824,0.0001203516,0.001659069,0.0001372964,0.0001881593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000213177,"about_ca_system_score_gemma":0.000008816459,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07713344,"about_ca_topic_score_gemma":0.0007703978,"domain_scores_codex":[0.9990897,0.00008319256,0.0001523929,0.0001618039,0.0002331285,0.000279757],"domain_scores_gemma":[0.9994748,0.00007571188,0.00006970413,0.0002516978,0.000007405863,0.0001207309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004418876,0.00002407573,0.876937,0.00001660795,0.000008890152,0.000002745749,0.0005903508,0.000001480117,0.00003754207,0.0005535018,0.003574995,0.1182086],"study_design_scores_gemma":[0.0001645147,0.0001100641,0.5929435,0.000001026851,0.000008995036,0.000002051798,0.00007677585,0.0005059455,0.0001471357,0.0001720829,0.4057882,0.00007968479],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3315247,0.000007584119,0.000004310699,0.0148981,0.00001352568,0.0002618633,0.00005399635,0.00003917503,0.6531968],"genre_scores_gemma":[0.9939829,0.001006564,0.0001105277,0.003490284,0.0003693387,0.00005439091,0.00001313929,0.00001733628,0.0009555933],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6624581,"threshold_uncertainty_score":0.9871807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04022273903171671,"score_gpt":0.2701967642050473,"score_spread":0.2299740251733306,"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."}}