{"id":"W2732290219","doi":"10.1111/faf.12235","title":"Options for integrating ecological, economic, and social objectives in evaluation and management of fisheries","year":2017,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Coquitlam College; Government of New Brunswick; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fisheries management; Corporate governance; Business; Context (archaeology); Environmental resource management; Ecosystem-based management; Fishery; Marine fisheries; Management by objectives; Environmental planning; Ecosystem; Ecology; Geography; Economics; Fish <Actinopterygii>; Fishing","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003565233,0.00008272759,0.000143767,0.00001824286,0.0004270308,0.0001709917,0.00009145481,0.00005444433,0.00060604],"category_scores_gemma":[0.00005415627,0.00007529991,0.00001734138,0.00001602411,0.0006371971,0.000424799,0.0003270636,0.00005692928,4.573033e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003578278,"about_ca_system_score_gemma":0.000006225327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003793518,"about_ca_topic_score_gemma":0.003814493,"domain_scores_codex":[0.9993874,0.00003151455,0.0001434466,0.000214486,0.00007916959,0.0001440191],"domain_scores_gemma":[0.9997401,0.00004722694,0.00007490713,0.0001001304,0.00000924477,0.00002838917],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007768039,0.00003399922,0.8438134,0.0001037936,0.00002011411,0.000001171003,0.001336095,0.000001061251,0.00003759899,0.001240583,0.002038683,0.1512959],"study_design_scores_gemma":[0.0005108495,0.0001240049,0.9713429,0.000006695972,0.00001184959,0.000001191438,0.002162676,0.001161742,0.00002483897,0.002885448,0.02167106,0.00009670514],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9219936,0.00001183083,0.00002023902,0.002143056,0.0000340802,0.0004169175,0.00002652604,0.000006110695,0.07534762],"genre_scores_gemma":[0.9968273,0.0005495194,0.001706302,0.00006303088,0.00002432524,0.0001834238,0.00001333885,0.000006450277,0.0006263144],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1511992,"threshold_uncertainty_score":0.6635713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04180910451244566,"score_gpt":0.3039003456933428,"score_spread":0.2620912411808971,"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."}}