{"id":"W2887051304","doi":"10.1111/faf.12314","title":"Impacts of anthropogenic and natural “extreme events” on global fisheries","year":2018,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Coral and Marine Ecosystems Studies","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Fisheries and Oceans Canada; Regent College; Entrust (Canada)","funders":"","keywords":"Fishing; Subsistence agriculture; Livelihood; Fishery; Business; Stock (firearms); Natural resource economics; Fisheries management; Natural disaster; Corporate governance; Geography; Environmental resource management; Economics; Agriculture; Finance","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":[0.0004818623,0.000265599,0.0001395959,0.000838861,0.0001849076,0.0006749047,0.0001442559,0.0002038963,0.002492499],"category_scores_gemma":[0.00164514,0.00007554018,0.0004697622,0.00108959,0.0004606683,0.0005327132,0.001150031,0.0002638786,0.0001751727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003544389,"about_ca_system_score_gemma":0.000264447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00733816,"about_ca_topic_score_gemma":0.01130528,"domain_scores_codex":[0.9996768,0.000114563,0.00003124895,0.00004797182,0.00005487784,0.00007462865],"domain_scores_gemma":[0.9985752,0.0003259397,0.0006924745,0.0001112878,0.0001460142,0.0001490662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005126346,0.00002607442,0.9915011,0.00005146773,0.0001410538,0.00009727928,0.00008435666,0.002252238,0.0003110806,0.0002064009,0.0004431003,0.00483455],"study_design_scores_gemma":[0.000001268216,0.00003666697,0.9982033,0.00001486844,0.00001955719,0.00003742476,0.000354126,0.0005935258,0.0001024038,0.0001251687,0.0005079696,0.000003681523],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951482,0.0002352196,0.0002940851,0.0001359584,0.00001235869,0.000009603647,0.001807056,0.00001224601,0.002345243],"genre_scores_gemma":[0.9988877,0.000187708,0.0001164641,0.0000248676,0.00001021573,0.000005956782,0.0006344422,0.000002952919,0.0001296615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00733816,"threshold_uncertainty_score":0.01459092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01291634738093513,"score_gpt":0.2164780582869605,"score_spread":0.2035617109060254,"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."}}