{"id":"W2516219190","doi":"10.1093/icesjms/fsw127","title":"Effectiveness of lobster fisheries management in New Zealand and Nova Scotia from multi-species and ecosystem perspectives","year":2016,"lang":"en","type":"article","venue":"ICES Journal of Marine Science","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Fisheries and Oceans Canada; Dalhousie University","funders":"","keywords":"Fishery; Maximum sustainable yield; Fisheries management; Stock assessment; Ecosystem; Nova scotia; Marine ecosystem; Ecosystem-based management; Environmental science; Geography; Ecology; Fishing; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0009084528,0.0005732862,0.0003769243,0.0005807678,0.0004790842,0.001406124,0.000703257,0.0004354244,0.001191449],"category_scores_gemma":[0.002643741,0.0002953319,0.0005918305,0.0003759647,0.0006336989,0.0007308637,0.0007232109,0.0003122131,0.00007016851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006635821,"about_ca_system_score_gemma":0.00359652,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6310462,"about_ca_topic_score_gemma":0.7324402,"domain_scores_codex":[0.9996866,0.00006225346,0.00001892515,0.00004883009,0.00005083975,0.0001324642],"domain_scores_gemma":[0.9991176,0.0002507506,0.0002120676,0.00004547716,0.0001589496,0.000215068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0004375179,0.0001680621,0.3687569,0.000181058,0.0004374128,0.0005621909,0.0002289387,0.6116354,0.003602203,0.001238328,0.0007095685,0.01204235],"study_design_scores_gemma":[0.000220109,0.0007828807,0.4533945,0.0002334912,0.0004617283,0.0001802403,0.001977071,0.5380964,0.001815073,0.001081008,0.001660655,0.00009685659],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971751,0.0001834984,0.0001532453,0.00008844865,0.000004998343,0.00001270692,0.0001385473,0.00001009304,0.002233222],"genre_scores_gemma":[0.9992124,0.0001283976,0.0001853696,0.00002551963,0.000001011588,0.000005817554,0.00007401137,0.000003718568,0.0003637479],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3689538,"threshold_uncertainty_score":0.7422532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01626892558392466,"score_gpt":0.2531654312438154,"score_spread":0.2368965056598908,"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."}}