{"id":"W3207065284","doi":"10.5539/jas.v13n11p153","title":"Effect of Coronavirus on Aquaculture in Oyo state, Nigeria","year":2021,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Aquaculture; Respondent; Nonprobability sampling; Pandemic; Socioeconomics; Socioeconomic status; Fish farming; Business; Coronavirus; Agriculture; Descriptive statistics; Agricultural science; Coronavirus disease 2019 (COVID-19); Geography; Fishery; Environmental health; Fish <Actinopterygii>; Economics; Biology; Population; Political science; Medicine; Statistics; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0003350261,0.0001317555,0.0001239323,0.0002660699,0.0008349467,0.0006028346,0.00009110066,0.0002614088,0.002101282],"category_scores_gemma":[0.0008903061,0.000117774,0.000123629,0.0002909609,0.0005012086,0.0003747265,0.0005225669,0.0003134281,0.000108367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007327997,"about_ca_system_score_gemma":0.001080593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01093759,"about_ca_topic_score_gemma":0.03004386,"domain_scores_codex":[0.999821,0.00005586184,0.00001511887,0.00001864891,0.00002888896,0.00006047356],"domain_scores_gemma":[0.9994637,0.0001436932,0.000218471,0.000008044554,0.00005484872,0.0001112569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001439582,0.0003301526,0.9694287,0.0002771949,0.00001853677,0.003068029,0.008318944,0.0001303613,0.001930514,0.0005359427,0.0007195691,0.01509804],"study_design_scores_gemma":[0.000004748799,0.0002707266,0.9645916,0.0001880243,0.00001270936,0.0005683997,0.03189336,0.00007887013,0.0001670765,0.0001793856,0.002037393,0.000007776605],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973182,0.0003538938,0.00001296447,0.0003355079,0.000008392714,0.00000644381,0.00002369724,4.658337e-7,0.001940395],"genre_scores_gemma":[0.9984446,0.0008120288,0.00003303169,0.00006983573,0.000004990603,0.00000516059,0.00001569976,3.71543e-7,0.0006143362],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01093759,"threshold_uncertainty_score":0.02174783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02541346233620374,"score_gpt":0.2805564164211428,"score_spread":0.2551429540849391,"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."}}