{"id":"W3170340212","doi":"10.5751/es-12117-260226","title":"Opportunities and impediments for use of local data in the management of salmon fisheries","year":2021,"lang":"en","type":"article","venue":"Ecology and Society","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"College of Engineering, Michigan State University; Michigan State University; University of Washington; Gordon and Betty Moore Foundation","keywords":"Fisheries management; Fishery; Fisheries science; Geography; Environmental resource management; Fishing; Business; Economics; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.4242472,0.001520202,0.00197273,0.007923175,0.005379128,0.01445165,0.008780504,0.008673944,0.009719769],"category_scores_gemma":[0.4908124,0.002716567,0.001977907,0.008052087,0.01522695,0.03113589,0.03016198,0.01956525,0.004089608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0070804,"about_ca_system_score_gemma":0.02892755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0313285,"about_ca_topic_score_gemma":0.03497226,"domain_scores_codex":[0.6942751,0.2052132,0.02891461,0.01265996,0.05211917,0.006817974],"domain_scores_gemma":[0.2404848,0.5719113,0.03854623,0.04236905,0.08531499,0.0213737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0009526724,0.0004233556,0.06972157,0.004806188,0.0004758724,0.0009196267,0.009884096,0.004398257,0.001669807,0.04317393,0.1144655,0.7491091],"study_design_scores_gemma":[0.0005531334,0.001227709,0.08499124,0.03058816,0.0005870074,0.003482478,0.04968031,0.01847371,0.005383543,0.2387326,0.5643501,0.001950042],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.03122511,0.03125267,0.03547086,0.882532,0.001779991,0.0005532419,0.001483772,0.0005159327,0.01518648],"genre_scores_gemma":[0.5983104,0.06416879,0.2416526,0.07771924,0.005957407,0.003109762,0.002326821,0.0007729706,0.005982059],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4242472,"threshold_uncertainty_score":0.7100057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09400958199443954,"score_gpt":0.3055417311562795,"score_spread":0.21153214916184,"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."}}