{"id":"W4411986714","doi":"10.26686/wgtn.29474252","title":"Extreme Weather and The Economics of Fisheries","year":2025,"lang":"en","type":"dissertation","venue":"","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Victoria University; Victoria University of Wellington; University of Otago","keywords":"Extreme weather; Fishery; Geography; Climatology; Environmental science; Meteorology; Data science; Oceanography; Computer science; Climate change; Geology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003023199,0.000161053,0.0001146783,0.0003227668,0.0002759034,0.001382757,0.0001495574,0.0004670579,0.003906194],"category_scores_gemma":[0.001395904,0.00007956671,0.0001718779,0.0004959747,0.001087083,0.001725035,0.0005503217,0.0005475565,0.0002510652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007791292,"about_ca_system_score_gemma":0.000356457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003719356,"about_ca_topic_score_gemma":0.002507609,"domain_scores_codex":[0.9998491,0.0000614081,0.000006124495,0.00001527837,0.00002893262,0.00003913792],"domain_scores_gemma":[0.9995735,0.0002128191,0.00009974631,0.00002408278,0.00004472552,0.00004519192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001191702,0.00006616653,0.03279009,0.0001741393,0.0001060899,0.0004362995,0.0006596347,0.0211785,0.0006186211,0.8313743,0.02288558,0.08959135],"study_design_scores_gemma":[0.0000236801,0.0001218115,0.1447311,0.0006020609,0.00003245035,0.0002144071,0.003114176,0.01164949,0.0003442956,0.6996667,0.1394384,0.00006154618],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5215866,0.05471639,0.01154802,0.06561507,0.001270097,0.0000469454,0.0009077829,0.00003592916,0.3442732],"genre_scores_gemma":[0.9710305,0.01505823,0.0003905263,0.0008657068,0.000429542,0.00001220973,0.00008405458,0.000006898541,0.0121223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003906194,"threshold_uncertainty_score":0.01306748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01667517353657939,"score_gpt":0.2247513604427159,"score_spread":0.2080761869061365,"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."}}