{"id":"W3206392632","doi":"","title":"ECONOMIC IMPLICATIONS OF FOOD CONSUMPTION BEHAVIOR CHANGES IN ROMANIA DURING THE COVID-19 PANDEMIC","year":2021,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Consumption (sociology); Recession; Context (archaeology); Quarter (Canadian coin); Pandemic; Agriculture; Coronavirus disease 2019 (COVID-19); Index (typography); Agricultural economics; Economics; Economic sector; Food consumption; Business; Development economics; Geography; Economy; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006838702,0.0001026054,0.0002071652,0.0006076064,0.0002867649,0.0009258497,0.000178223,0.0003347959,0.001909453],"category_scores_gemma":[0.002433066,0.000111368,0.0002261761,0.001124678,0.0003489778,0.0003822903,0.0006457723,0.0005720862,0.0001694256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001290546,"about_ca_system_score_gemma":0.0005638232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02176591,"about_ca_topic_score_gemma":0.01849575,"domain_scores_codex":[0.9996607,0.0001418063,0.00002041649,0.00003288843,0.00003052164,0.000113718],"domain_scores_gemma":[0.999411,0.0001753796,0.0002555278,0.00002457491,0.00006902227,0.00006454688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003313344,0.0001598515,0.9706365,0.00008733699,0.00007156573,0.001455928,0.001213833,0.006872617,0.0006837514,0.004416684,0.002661543,0.01140907],"study_design_scores_gemma":[0.00000721273,0.00005204733,0.9898113,0.00004189473,0.00001349686,0.0001354606,0.002823159,0.004356857,0.0001592426,0.0003499406,0.002239307,0.00001014852],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960237,0.0002668546,0.00007176962,0.0005949062,0.000008426287,0.000007771117,0.0005107885,0.000002033962,0.002513858],"genre_scores_gemma":[0.9989643,0.0002546297,0.00005653348,0.00004259589,0.000008514061,0.000004130349,0.0003128315,0.000001640741,0.0003549104],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02176591,"threshold_uncertainty_score":0.04327846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4196865038945295,"score_gpt":0.5209284810096415,"score_spread":0.101241977115112,"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."}}