{"id":"W7116665869","doi":"10.2139/ssrn.5946504","title":"Global Fisheries: Socio-economic Impacts of Overfishing","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Overfishing; Fish stock; Fishing; Maximum sustainable yield; Stock (firearms); Sustainable yield; Sustainability; Bioeconomics; Fish <Actinopterygii>","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":[0.0004584193,0.0002285808,0.0002353435,0.0006959102,0.0002412045,0.001956388,0.000130274,0.0009048092,0.02231769],"category_scores_gemma":[0.002563918,0.00009046188,0.0002254114,0.002016724,0.000638805,0.001559186,0.0008028486,0.0006855145,0.0008405317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007058373,"about_ca_system_score_gemma":0.0005008381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009651803,"about_ca_topic_score_gemma":0.008953693,"domain_scores_codex":[0.9998547,0.00004726926,0.000006138956,0.00001807659,0.00004567363,0.00002804606],"domain_scores_gemma":[0.9991534,0.0004238855,0.0001583993,0.00004079711,0.000113426,0.0001100864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0004730598,0.0002314262,0.1975187,0.001077234,0.0004745724,0.001707503,0.002447615,0.02934469,0.003263965,0.4444945,0.1435559,0.1754109],"study_design_scores_gemma":[0.000038891,0.0001195333,0.4046351,0.0004878957,0.0002912136,0.000576631,0.005614422,0.01227452,0.000677895,0.4841952,0.09102727,0.00006134825],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6114007,0.03122166,0.006884616,0.1140238,0.001925735,0.00001851405,0.006574116,0.0001610869,0.2277897],"genre_scores_gemma":[0.9808757,0.008302792,0.0003214002,0.0007474981,0.0005205882,0.000006208352,0.0003976488,0.00002826479,0.008799991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02231769,"threshold_uncertainty_score":0.07466018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009480451591826962,"score_gpt":0.2654788200098118,"score_spread":0.2559983684179848,"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."}}