{"id":"W3086391656","doi":"10.1093/icesjms/fsaa109","title":"Regulation strength and technology creep play key roles in global long-term projections of wild capture fisheries","year":2020,"lang":"en","type":"article","venue":"ICES Journal of Marine Science","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"H2020 European Research Council; European Commission","keywords":"Overfishing; Climate change; Natural resource economics; Fishing; Global warming; Fisheries management; Effects of global warming; Spillover effect; Environmental science; Fishery; Economics; Ecology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001529966,0.0002954142,0.0002346118,0.0004623371,0.0003717363,0.001696406,0.0005314694,0.0009548577,0.001838868],"category_scores_gemma":[0.004798873,0.0002731575,0.0007096214,0.0003609452,0.0009454564,0.002180369,0.001076594,0.0009262344,0.0001517196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001073788,"about_ca_system_score_gemma":0.0006687932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.014882,"about_ca_topic_score_gemma":0.009911573,"domain_scores_codex":[0.9997823,0.00006877806,0.0000150769,0.00006412814,0.00002635476,0.00004332614],"domain_scores_gemma":[0.9986703,0.0005722029,0.0003727481,0.0001238683,0.0001548186,0.0001061023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005388416,0.0000448047,0.09105593,0.000036155,0.00009438107,0.0001708056,0.00007839045,0.8817309,0.001943674,0.0188782,0.0004918411,0.00542095],"study_design_scores_gemma":[0.00001868244,0.00009897054,0.07502427,0.00003754421,0.00006269999,0.00007223211,0.0003954454,0.8951006,0.0006478999,0.02719507,0.001285908,0.00006072272],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9766766,0.0002443232,0.01618201,0.001353305,0.00002324957,0.00001607305,0.0002637937,0.00005268593,0.005187967],"genre_scores_gemma":[0.9990509,0.00007096956,0.000458321,0.00003654391,0.000002967022,0.000004867584,0.00005251164,0.000005674216,0.0003172507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.014882,"threshold_uncertainty_score":0.02959073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01114835939356185,"score_gpt":0.2524802920978528,"score_spread":0.241331932704291,"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."}}