{"id":"W2157633368","doi":"10.1111/j.1467-2979.2011.00450.x","title":"Contribution of marine fisheries to worldwide employment","year":2011,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Coral and Marine Ecosystems Studies","field":"Environmental Science","cited_by":452,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Institut Français de Recherche pour l'Exploitation de la Mer","keywords":"Fishing; Fishery; Marine fisheries; Fisheries management; Business; Scale (ratio); Fisheries law; Marine fish; Fish <Actinopterygii>; Geography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007897698,0.0001084248,0.0001842522,0.00001734494,0.0000889637,0.00001383151,0.00008198161,0.00002709334,0.002424995],"category_scores_gemma":[0.00005441823,0.00009106966,0.00002961743,0.000114567,0.0001247367,0.0001586362,0.0004998065,0.00003788322,0.00003116797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002372134,"about_ca_system_score_gemma":0.000002522291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002390455,"about_ca_topic_score_gemma":0.008871992,"domain_scores_codex":[0.9993343,0.00001471816,0.0001845029,0.0001766027,0.0001083425,0.0001814994],"domain_scores_gemma":[0.9997147,0.00001675615,0.0000511453,0.0001222325,0.00001676828,0.00007835733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007339034,0.00003544393,0.9479204,0.000010448,0.00001333582,0.00000280337,0.0009474668,9.969812e-8,0.0001592894,0.0001200399,0.03760668,0.01311062],"study_design_scores_gemma":[0.000136264,0.0001830104,0.8408421,0.000008057428,0.0000090798,0.000002770132,0.0001481305,0.000002600236,0.001330484,0.0007792473,0.1564519,0.0001063719],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9416496,0.00001153672,0.00004921692,0.001438577,0.0001460375,0.0001916035,0.00001672464,0.0000361782,0.05646051],"genre_scores_gemma":[0.9952377,0.00003879169,0.0004805974,0.000466789,0.00002470713,0.00004177219,0.000008087683,0.00000658379,0.003694942],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1188452,"threshold_uncertainty_score":0.9984869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01530372112708935,"score_gpt":0.1895866641831812,"score_spread":0.1742829430560918,"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."}}