{"id":"W2479667179","doi":"","title":"Reconstruction of marine fisheries catches for New Zealand (1950-2010)","year":2015,"lang":"en","type":"article","venue":"ResearchSpace (University of Auckland)","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Fishery; Geography; Fishing; Marine fisheries; Oceanography; Geology; Biology","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":[0.0007322925,0.0009885267,0.0003606676,0.009162598,0.0004008187,0.001069843,0.0006415035,0.0002849624,0.005293577],"category_scores_gemma":[0.003166768,0.0005159754,0.001121468,0.009081612,0.0004841049,0.001442575,0.001207352,0.0006634305,0.00178685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00743342,"about_ca_system_score_gemma":0.004199535,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7237487,"about_ca_topic_score_gemma":0.6674022,"domain_scores_codex":[0.9992275,0.00002235569,0.0001178092,0.0001681423,0.0003599196,0.0001042423],"domain_scores_gemma":[0.9979113,0.00005621784,0.0007602184,0.0001008315,0.001026526,0.0001448428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004789873,0.0001131385,0.7252487,0.00218597,0.001034343,0.001508608,0.002988656,0.01225334,0.005740193,0.004212041,0.1001052,0.1441309],"study_design_scores_gemma":[0.00001316171,0.00003719173,0.956259,0.0000980613,0.00005625524,0.0002137997,0.0005128746,0.001600263,0.0002673485,0.0001279233,0.04077584,0.00003826781],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.61054,0.003784228,0.003872724,0.001002659,0.000146859,0.0002606405,0.3385269,0.0006502,0.04121578],"genre_scores_gemma":[0.7252699,0.005470242,0.009346976,0.0001291972,0.00004784542,0.0004282172,0.2419182,0.0001586964,0.01723076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7237487,"threshold_uncertainty_score":0.5557564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04539533546075519,"score_gpt":0.240964141992298,"score_spread":0.1955688065315428,"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."}}