{"id":"W4220892628","doi":"10.34123/icdsos.v2021i1.226","title":"Household Food Insecurity in DKI Jakarta Province at The Beginning of The Covid-19 Pandemic","year":2022,"lang":"en","type":"article","venue":"Proceedings of The International Conference on Data Science and Official Statistics","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pandemic; Poverty; Quarter (Canadian coin); Coronavirus disease 2019 (COVID-19); Socioeconomics; Socioeconomic status; Food security; Food insecurity; Geography; Economic growth; Development economics; Environmental health; Population; Economics; Agriculture; Medicine; Infectious disease (medical specialty); Disease","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":[0.0002746911,0.0001747152,0.0002092162,0.0005746048,0.0008553389,0.001219121,0.0002687287,0.0002848665,0.00235053],"category_scores_gemma":[0.001001942,0.0001624913,0.0003415066,0.001303175,0.0004308424,0.0004471341,0.0007594581,0.0009683033,0.0003137456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001626815,"about_ca_system_score_gemma":0.001261648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1695347,"about_ca_topic_score_gemma":0.2077489,"domain_scores_codex":[0.9997717,0.00004622629,0.00001794184,0.00002816716,0.00003298195,0.0001029777],"domain_scores_gemma":[0.999355,0.0001266608,0.0002087848,0.00002141355,0.00008341239,0.0002046532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006299088,0.0000607151,0.9954348,0.00001724126,0.00002636945,0.0003909077,0.001156009,0.0002919223,0.000121562,0.0001568675,0.0005005596,0.001780075],"study_design_scores_gemma":[0.000001159395,0.00002384234,0.9917886,0.00002440606,0.00001181695,0.0000943355,0.007179101,0.0003625594,0.00007439062,0.0000384136,0.000394859,0.000006542426],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998047,0.0001354167,0.00002097329,0.0001919098,0.000007874134,0.000004757834,0.0005409759,0.000001453908,0.001049716],"genre_scores_gemma":[0.9990355,0.000132509,0.00001693069,0.00002211247,0.000003609834,0.000003496683,0.000339101,7.826559e-7,0.0004461322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1695347,"threshold_uncertainty_score":0.3370957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2256079897308465,"score_gpt":0.3223371010639919,"score_spread":0.0967291113331454,"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."}}