{"id":"W3048312104","doi":"10.1002/fsh.10512","title":"Knowledge co-production: A pathway to effective fisheries management, conservation, and governance","year":2020,"lang":"en","type":"article","venue":"Fisheries","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":172,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor; University of Ottawa; The Scarborough Hospital; University of British Columbia; University of Toronto; Fisheries and Oceans Canada; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Genome British Columbia; Genome Canada","keywords":"Business; Corporate governance; Production (economics); Fishery; Fisheries management; Fisheries law; Environmental resource management; Environmental planning; Geography; Environmental science; Biology; Economics; Finance; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.06975305,0.001099767,0.001075607,0.004964035,0.01143339,0.03459018,0.004841424,0.01472962,0.01315652],"category_scores_gemma":[0.06283152,0.000918734,0.001280891,0.004895302,0.05409727,0.040526,0.05665463,0.01182922,0.002578569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01231138,"about_ca_system_score_gemma":0.06315064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005681245,"about_ca_topic_score_gemma":0.005974185,"domain_scores_codex":[0.9528998,0.03330771,0.001400988,0.003059213,0.005628288,0.00370407],"domain_scores_gemma":[0.8814069,0.06354465,0.006609694,0.0177153,0.01430651,0.01641695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006427354,0.0003655783,0.003835598,0.0008518968,0.00007585946,0.0009611256,0.02419587,0.002214361,0.0006758463,0.7906514,0.02940924,0.1466988],"study_design_scores_gemma":[0.00003254471,0.00009719557,0.001281143,0.001994206,0.0000227604,0.0002817755,0.02322556,0.00166352,0.0006368224,0.8099263,0.1607705,0.00006778709],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02874304,0.009033257,0.1899816,0.4902247,0.001647505,0.001054192,0.0001329773,0.0005302703,0.2786524],"genre_scores_gemma":[0.8663177,0.00602377,0.09608884,0.01525992,0.0006867932,0.0009238988,0.0001324141,0.0001759837,0.01439079],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9885666,"threshold_uncertainty_score":0.3688938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01327578040767676,"score_gpt":0.2054480343945714,"score_spread":0.1921722539868946,"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."}}