{"id":"W6958635288","doi":"10.6084/m9.figshare.23207812","title":"Additional file 2 of Prevalence and sociodemographic correlates of food insecurity among post-secondary students and non-students of similar age in Canada","year":2023,"lang":"en","type":"article","venue":"Figshare","topic":"Legal and Regulatory Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Food insecurity; Population; Epidemiology; Logistic regression","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009285737,0.0007316293,0.001151361,0.004243846,0.002502454,0.002218237,0.002129724,0.0008616627,0.729929],"category_scores_gemma":[0.01777887,0.0006812461,0.001191852,0.01023418,0.0004948149,0.00130129,0.001032435,0.000965004,0.05498083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008394747,"about_ca_system_score_gemma":0.02599993,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8944251,"about_ca_topic_score_gemma":0.9162679,"domain_scores_codex":[0.9992119,0.00005573801,0.0001003482,0.0001311719,0.0002227814,0.0002780893],"domain_scores_gemma":[0.9850771,0.005327498,0.0009670925,0.0007795138,0.006801382,0.001047547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001560259,0.0001190233,0.01861678,0.00091792,0.00004746801,0.00007183181,0.0001843294,0.0003309394,0.00002855915,0.0006809722,0.9707451,0.008101056],"study_design_scores_gemma":[0.002410964,0.0001476312,0.4579276,0.0036533,0.0001944533,0.0004316581,0.003773286,0.002295927,0.0003790097,0.003411894,0.5251489,0.0002253038],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0007194533,0.00001354728,0.00004501997,0.00005562093,0.00001371093,0.0000879771,0.9976171,0.00004779748,0.001399781],"genre_scores_gemma":[0.02844757,0.0001979988,0.001792318,0.0003711247,0.00004611654,0.001593187,0.9468352,0.0002086754,0.02050784],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.729929,"threshold_uncertainty_score":0.3852234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01349315752765304,"score_gpt":0.2447168550498496,"score_spread":0.2312236975221966,"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."}}