{"id":"W2239064769","doi":"10.1371/journal.pone.0145285","title":"Projected Scenarios for Coastal First Nations’ Fisheries Catch Potential under Climate Change: Management Challenges and Opportunities","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Climate change; Abundance (ecology); Species richness; Latitude; Range (aeronautics); Geography; Relative species abundance; Subsistence agriculture; Marine protected area; Fisheries management; Fishery; Ecology; Fisheries science; Environmental science; Fishing; Biology; Habitat","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00135656,0.0007209919,0.000298382,0.0006512192,0.0006525935,0.001225255,0.0009689421,0.0009013321,0.001922862],"category_scores_gemma":[0.001626635,0.0002988025,0.0006213082,0.00103736,0.0003774556,0.0007839301,0.0006702284,0.0006742139,0.0002247774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004304044,"about_ca_system_score_gemma":0.002967302,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2152435,"about_ca_topic_score_gemma":0.2799048,"domain_scores_codex":[0.9996169,0.0001546271,0.00001318359,0.00003904436,0.00008198787,0.00009423256],"domain_scores_gemma":[0.9993962,0.0001631216,0.00006689253,0.00002513386,0.0002268061,0.0001219044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003236973,0.00008733515,0.05912659,0.00009590618,0.0001092373,0.0003130339,0.0001000061,0.9228523,0.001178158,0.003027046,0.003413681,0.009373019],"study_design_scores_gemma":[0.0001161844,0.0003758303,0.06811916,0.00007274285,0.0001252098,0.0001417239,0.001769691,0.9145517,0.001188163,0.006510946,0.006914875,0.0001137872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9596971,0.0005713663,0.008491157,0.002461098,0.00006148225,0.0001270204,0.007811081,0.0002328545,0.02054684],"genre_scores_gemma":[0.9918805,0.0003270963,0.00341353,0.00009639826,0.000006030887,0.0001201555,0.00291447,0.00001428901,0.001227521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7847565,"threshold_uncertainty_score":0.4279813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1413720787322653,"score_gpt":0.25082814136101,"score_spread":0.1094560626287447,"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."}}