{"id":"W2546817479","doi":"10.1111/faf.12192","title":"A typology of fisheries management tools: using experience to catalyse greater success","year":2016,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Coral and Marine Ecosystems Studies","field":"Environmental Science","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Norges Forskningsråd; European Commission; Rockefeller Foundation","keywords":"Fishing; Fisheries management; Business; Scale (ratio); Environmental resource management; Livelihood; Typology; Fishery; Corporate governance; Affect (linguistics); Geography; 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":[],"consensus_categories":[],"category_scores_codex":[0.0000521949,0.0001233317,0.0001901526,0.00002436869,0.0001066895,0.00002860693,0.0001373943,0.00003131417,0.000912167],"category_scores_gemma":[0.00002635273,0.00008077114,0.000027512,0.0001149255,0.0002814765,0.0003611213,0.0006198555,0.00002019317,0.00002094165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003198344,"about_ca_system_score_gemma":0.000002082426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008275433,"about_ca_topic_score_gemma":0.001210899,"domain_scores_codex":[0.9992106,0.00001682421,0.0001805085,0.0002603387,0.0001096961,0.0002220571],"domain_scores_gemma":[0.9996731,0.00002428052,0.00004880441,0.0001769278,0.000009591497,0.00006725735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006155464,0.00001794638,0.9629309,0.00003796544,0.0000227133,0.00001328136,0.002187204,3.894629e-7,0.001329739,0.00005908754,0.009139991,0.02419921],"study_design_scores_gemma":[0.0002634153,0.0001401246,0.8934729,0.0000466526,0.00001980753,0.00001595348,0.00146346,0.000004431541,0.003300195,0.0001825988,0.1008503,0.0002401642],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850618,0.00001017591,0.0001222973,0.001420341,0.0001451536,0.0001475391,0.00002403816,0.00002264289,0.01304606],"genre_scores_gemma":[0.9959737,0.00003905654,0.0004900715,0.0003034253,0.00002354618,0.00004350336,0.000001318634,0.000007372427,0.003118012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09171027,"threshold_uncertainty_score":0.9987589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03163554209445756,"score_gpt":0.2327992248031692,"score_spread":0.2011636827087116,"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."}}