{"id":"W3184959754","doi":"10.1111/faf.12595","title":"Climate change adaptation in fisheries","year":2021,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Coral and Marine Ecosystems Studies","field":"Environmental Science","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Social Science Research Council","keywords":"Climate change; Fisheries management; Livelihood; Fishing; Fisheries science; Diversification (marketing strategy); Environmental resource management; Adaptation (eye); Adaptive management; Fisheries law; Global warming; Fishery; Geography; Adaptive capacity; Ecological forecasting; Ecology; Business; Environmental science; Biology; Agriculture","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":[],"consensus_categories":[],"category_scores_codex":[0.00853877,0.0005505279,0.001193147,0.009829048,0.00057753,0.002279395,0.0006153317,0.001028463,0.002995424],"category_scores_gemma":[0.02657868,0.0003137265,0.002434573,0.01286645,0.0008651402,0.002339515,0.001508225,0.0008318381,0.0001857655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002316219,"about_ca_system_score_gemma":0.007788271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0123842,"about_ca_topic_score_gemma":0.02427984,"domain_scores_codex":[0.9950395,0.002489699,0.001160845,0.0005157443,0.0006256294,0.0001686103],"domain_scores_gemma":[0.9772774,0.01654193,0.003325754,0.0004971031,0.002163566,0.0001943184],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000153214,0.00007591578,0.06664135,0.3788493,0.0112656,0.0008168542,0.004572845,0.003109161,0.001057894,0.01035392,0.01619442,0.5069096],"study_design_scores_gemma":[0.00006103292,0.000279312,0.2055951,0.5291449,0.01343403,0.001180217,0.008272734,0.0009116434,0.0008270084,0.009426731,0.2307024,0.0001650235],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01428454,0.9757515,0.001120931,0.003433828,0.0005707294,0.0001691119,0.001661241,0.00001898082,0.002989065],"genre_scores_gemma":[0.2123924,0.7789323,0.003295839,0.003264332,0.0004180415,0.0003782658,0.0008788336,0.00001290403,0.0004271393],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.0123842,"threshold_uncertainty_score":0.04515785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03452358704151469,"score_gpt":0.1987407998775721,"score_spread":0.1642172128360574,"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."}}