{"id":"W2111159550","doi":"","title":"Identification and prioritization of food insecurity and vulnerability indices in iran.","year":2015,"lang":"en","type":"article","venue":"PubMed","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Delphi method; Food security; Per capita; Prioritization; Environmental health; Vulnerability (computing); Food insecurity; Business; Medicine; Socioeconomics; Geography; Agriculture; Economics; Population; Statistics; Computer security; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007686822,0.0003245107,0.0003528727,0.003008945,0.0009270709,0.0009609029,0.000543452,0.0003828477,0.001130968],"category_scores_gemma":[0.008652759,0.0002011104,0.0004761216,0.001620283,0.000680858,0.0007886217,0.001546329,0.0006558513,0.00009374697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002312572,"about_ca_system_score_gemma":0.005196465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004642155,"about_ca_topic_score_gemma":0.007529781,"domain_scores_codex":[0.9970727,0.001351783,0.0002621618,0.0001657071,0.0007791836,0.0003684247],"domain_scores_gemma":[0.996082,0.00153804,0.0008265936,0.0000726782,0.00103694,0.0004437261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004712539,0.0004215383,0.6046179,0.002424467,0.0001882227,0.0008146429,0.03844224,0.001321424,0.003426144,0.004281488,0.004756415,0.3388343],"study_design_scores_gemma":[0.00006666178,0.0008839369,0.8483381,0.001440552,0.0001683569,0.00153735,0.121043,0.00510148,0.002322339,0.006571215,0.01241862,0.000108431],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98406,0.001829801,0.004225239,0.00249871,0.00005092534,0.0006410769,0.0002435576,0.00002252728,0.006428214],"genre_scores_gemma":[0.990306,0.0008186523,0.008067867,0.0001324921,0.00001158336,0.0002713051,0.0001326358,0.000002515583,0.0002569971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007686822,"threshold_uncertainty_score":0.04065228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2610087008153706,"score_gpt":0.4190490685172795,"score_spread":0.1580403677019088,"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."}}