{"id":"W4380875813","doi":"10.1002/9781119511847.ch16","title":"Rights‐Based Approaches to Fisheries Management","year":2023,"lang":"en","type":"other","venue":"","topic":"International Maritime Law Issues","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Human rights; Fisheries law; Fishing; Fisheries management; Fishery; Perspective (graphical); Fish <Actinopterygii>; Theme (computing); Political science; Transferability; Relevance (law); Business; Environmental resource management; Law and economics; Law; Economics; Economic growth; Computer science; Human capital","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":["insufficient_payload"],"category_scores_codex":[0.00005267112,0.0001642352,0.0001181131,0.0000672852,0.00003003032,0.00003533854,0.0003246717,0.0000796321,0.1266227],"category_scores_gemma":[0.000002818992,0.0001371251,0.00004282276,0.0001249819,0.00006610707,0.00003002805,0.0002489709,0.00004836929,0.03529191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001114233,"about_ca_system_score_gemma":0.000001083291,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008542245,"about_ca_topic_score_gemma":0.01743601,"domain_scores_codex":[0.999019,0.00001258841,0.00009435311,0.0003431803,0.0003568202,0.0001740456],"domain_scores_gemma":[0.9996414,0.00001551009,0.00003025785,0.0002558556,7.982777e-7,0.00005617166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000023971,0.00002188855,0.0002134701,0.00001158482,0.00002519525,0.0000177163,0.00001054199,0.00006054599,4.40001e-7,0.01548213,0.9830193,0.00113479],"study_design_scores_gemma":[0.00006080543,0.00001227146,0.0008102187,0.00003652553,0.000008972571,2.197936e-7,0.000005681844,0.0001011501,0.00004146536,0.001438247,0.9972907,0.0001937632],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000005929253,0.000003574718,0.00055816,0.001192678,0.0001808329,0.0003345522,0.00001892246,0.000636218,0.9970691],"genre_scores_gemma":[0.0004177582,0.000001558401,0.01595186,0.0005682781,0.00007794944,0.0001077514,0.00001672456,0.0003274271,0.9825307],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.09133078,"threshold_uncertainty_score":0.9980599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04375816754807135,"score_gpt":0.2192199619337522,"score_spread":0.1754617943856808,"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."}}