{"id":"W2921275323","doi":"10.1002/9781118392607.ch1","title":"Governance of marine fisheries and biodiversity conservation","year":2014,"lang":"en","type":"other","venue":"","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University; Fisheries and Oceans Canada","funders":"","keywords":"Corporate governance; Biodiversity; Convergence (economics); Fishery; Biodiversity conservation; Geography; Scale (ratio); Marine conservation; STREAMS; Political science; Environmental resource management; Ecology; Economics; Biology; Economic growth; Management","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":[0.0009469908,0.0002016524,0.000147833,0.0007193276,0.001767011,0.006900554,0.000414389,0.0008693695,0.006675887],"category_scores_gemma":[0.001421352,0.000114986,0.0001242736,0.001759276,0.005252218,0.002675324,0.003321684,0.000982445,0.0006303609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004304196,"about_ca_system_score_gemma":0.006750745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01173875,"about_ca_topic_score_gemma":0.01720156,"domain_scores_codex":[0.9990618,0.0004286079,0.00003201672,0.0001103059,0.000199703,0.0001675387],"domain_scores_gemma":[0.9995242,0.0001156647,0.0000978863,0.0000552236,0.00007378276,0.0001332332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002965912,0.000007597451,0.001396354,0.00004709087,0.000003274099,0.00004673145,0.00160136,0.0005389229,0.00006849781,0.9476998,0.01211365,0.03647383],"study_design_scores_gemma":[0.000003772918,0.0000127629,0.007556232,0.0005646176,0.000005478476,0.00008671449,0.004212068,0.0005839273,0.00009787928,0.3200761,0.6667904,0.0000099312],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01983893,0.01624151,0.006332105,0.02092749,0.0003219815,0.00004730157,0.00009254727,0.00004376279,0.9361544],"genre_scores_gemma":[0.8100916,0.03358811,0.005610917,0.003962797,0.0006705472,0.0001515333,0.0002196299,0.00005172702,0.1456531],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01173875,"threshold_uncertainty_score":0.03122932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005462871735604139,"score_gpt":0.1547010210780807,"score_spread":0.1492381493424766,"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."}}