{"id":"W3135733186","doi":"10.29219/fnr.v65.5501","title":"Factors determining household-level food insecurity during COVID-19 epidemic: a case of Wuhan, China","year":2021,"lang":"en","type":"article","venue":"Food & Nutrition Research","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; Balsillie School of International Affairs","funders":"","keywords":"Food security; Food insecurity; China; Coronavirus disease 2019 (COVID-19); Environmental health; Business; Social distance; Purchasing; Outbreak; Geography; Socioeconomics; Medicine; Infectious disease (medical specialty); Disease; Economics; Marketing; Agriculture","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":["metaepi_narrow","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.002805548,0.0002628425,0.0006066071,0.0007769117,0.004333241,0.0000318448,0.0003358087,0.0005644,0.0007822691],"category_scores_gemma":[0.005739725,0.0002790701,0.000202163,0.001477365,0.0002581742,0.0003162542,0.0005717699,0.002484331,0.00004266009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006857822,"about_ca_system_score_gemma":0.001799128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001740053,"about_ca_topic_score_gemma":0.009539807,"domain_scores_codex":[0.9925815,0.003301447,0.001246947,0.0006777869,0.0008603912,0.001331868],"domain_scores_gemma":[0.994615,0.002478052,0.0003398153,0.0007553025,0.0008522891,0.0009595866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002207844,0.007002553,0.6423092,0.07734738,0.0006861624,0.004093195,0.158325,0.000161075,0.005378382,0.07430052,0.02731542,0.0008732604],"study_design_scores_gemma":[0.02699774,0.008639816,0.5937626,0.007697443,0.0001977277,0.001230894,0.2085987,0.0008593723,0.01156657,0.07957535,0.05850193,0.00237176],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899549,0.001145796,0.0001163633,0.003650297,0.0004087513,0.001633811,0.002392423,0.000165908,0.0005317809],"genre_scores_gemma":[0.9974647,0.0003958441,0.0006019337,0.0003300746,0.0003619298,0.0004341228,0.0002225017,0.00005139242,0.0001375505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06964994,"threshold_uncertainty_score":0.9999661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7503339383654896,"score_gpt":0.5761971847827345,"score_spread":0.174136753582755,"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."}}