{"id":"W4293077400","doi":"10.1111/faf.12678","title":"Untangling social–ecological interactions: A methods portfolio approach to tackling contemporary sustainability challenges in fisheries","year":2022,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Sustainability and Climate Change Governance","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Fisheries and Oceans Canada","funders":"National Science Foundation of Sri Lanka; Horizon 2020 Framework Programme; H2020 European Research Council; Norges Forskningsråd; National Science Foundation; Vetenskapsrådet; Svenska Forskningsrådet Formas","keywords":"Fisheries management; Scope (computer science); Reflexivity; Sustainability; Portfolio; Process (computing); Scale (ratio); Management science; Fisheries Research; Dimension (graph theory); Computer science; Fisheries science; Environmental resource management; Fishery; Data science; Ecology; Business; Sociology; Fish <Actinopterygii>; Geography; Economics; Fishing","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1973387,0.002630634,0.001795868,0.01271966,0.004692251,0.01951904,0.006806185,0.005245792,0.006108657],"category_scores_gemma":[0.1548501,0.001446117,0.002457681,0.00803692,0.0220287,0.01859343,0.01792983,0.007729425,0.001585007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008097104,"about_ca_system_score_gemma":0.02049729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002214338,"about_ca_topic_score_gemma":0.00372533,"domain_scores_codex":[0.86352,0.1209134,0.00416372,0.003376502,0.007120116,0.0009063494],"domain_scores_gemma":[0.7400704,0.2217549,0.006450743,0.01719689,0.01169216,0.002834852],"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":[0.00005230396,0.000194652,0.002732154,0.001635509,0.000204968,0.0002745514,0.01800978,0.00385316,0.0006927336,0.7421144,0.004467607,0.2257682],"study_design_scores_gemma":[0.00003228076,0.00007431168,0.0006536258,0.002593771,0.00007873182,0.0002357179,0.00621368,0.008161683,0.0007384178,0.9046816,0.07648844,0.00004771266],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002850919,0.003850181,0.9610792,0.0152583,0.0003272944,0.001062045,0.0001272288,0.0001959614,0.01524889],"genre_scores_gemma":[0.03322012,0.002701713,0.9568612,0.001197349,0.0001684521,0.003726772,0.0001145956,0.000140924,0.001868794],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1973387,"threshold_uncertainty_score":0.9898244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0909931354211072,"score_gpt":0.3087945682689752,"score_spread":0.217801432847868,"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."}}