{"id":"W2602022672","doi":"10.1016/j.marpol.2017.03.013","title":"The best catch data that can possibly be? Rejoinder to Ye et al. “FAO's statistic data and sustainability of fisheries and aquaculture”","year":2017,"lang":"en","type":"article","venue":"Marine Policy","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Paul G. Allen Family Foundation","keywords":"Sustainability; Aquaculture; Fishery; Food security; Statistic; Value (mathematics); Fish <Actinopterygii>; Fisheries management; Political science; Geography; Fishing; Ecology; Statistics; Biology; Agriculture; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0007485293,0.000147335,0.0001760879,0.00002419053,0.0005658673,0.0004216711,0.001720309,0.00003743647,0.0003135685],"category_scores_gemma":[0.002136216,0.0001018916,0.000009557011,0.00009712491,0.001043036,0.0005145164,0.01641994,0.0001734659,0.000003248613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007066312,"about_ca_system_score_gemma":0.0001073097,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2802399,"about_ca_topic_score_gemma":0.1164522,"domain_scores_codex":[0.9985049,0.00008275733,0.0001736268,0.0005289951,0.000338865,0.0003708638],"domain_scores_gemma":[0.9965436,0.0001421369,0.00009197788,0.003000875,0.00002729812,0.0001940941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004428876,0.00003465158,0.8337433,0.00003529585,0.00001520595,0.000008608587,0.0004847384,3.498018e-7,0.00001085217,0.0004670138,0.06100929,0.1041465],"study_design_scores_gemma":[0.0001615328,0.00006574774,0.5256546,0.000001951272,0.000007910005,0.000008154531,0.0005691281,0.0002406995,0.000007395131,0.001597315,0.4715815,0.0001040392],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.367913,0.00003149787,0.0001356786,0.4486852,0.00007278541,0.001227282,0.002618997,0.00002901545,0.1792865],"genre_scores_gemma":[0.9782343,0.0006860762,0.0008403431,0.002676044,0.00005262769,0.00002361398,0.00039809,0.00002521109,0.0170637],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6103213,"threshold_uncertainty_score":0.9915351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06161850395187624,"score_gpt":0.3594357422085316,"score_spread":0.2978172382566553,"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."}}