{"id":"W6901984862","doi":"10.6084/m9.figshare.23207812.v1","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":"Food Security and Health in Diverse Populations","field":"Health Professions","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":[0.000886654,0.0007449463,0.001261804,0.0041679,0.002313567,0.002165316,0.00220614,0.0008907735,0.736652],"category_scores_gemma":[0.01800203,0.0007106639,0.001257961,0.01000385,0.0004775033,0.001381492,0.001101801,0.0009484757,0.05640414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007556415,"about_ca_system_score_gemma":0.02214485,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8613157,"about_ca_topic_score_gemma":0.8957182,"domain_scores_codex":[0.9992521,0.0000512645,0.0001048774,0.0001314044,0.0001975404,0.0002628684],"domain_scores_gemma":[0.985472,0.005371634,0.001014939,0.0007385212,0.006377854,0.00102504],"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":[0.0001936239,0.0001321559,0.02069804,0.001450324,0.00006518954,0.0000847866,0.0001537196,0.0003992085,0.00003379929,0.0005762185,0.9665968,0.009616074],"study_design_scores_gemma":[0.003577023,0.0001919901,0.4821914,0.004927849,0.0002614123,0.0005719731,0.00304336,0.002577623,0.0003962452,0.003556985,0.4984457,0.0002584977],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.00055529,0.00001513982,0.00003755027,0.00004625105,0.00001380155,0.00008687295,0.9981172,0.00004335472,0.001084618],"genre_scores_gemma":[0.02363257,0.0002225472,0.001498487,0.0003892696,0.00005375631,0.001545885,0.9559969,0.0001838649,0.01647665],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.736652,"threshold_uncertainty_score":0.375634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07884127132613794,"score_gpt":0.3654687037902869,"score_spread":0.286627432464149,"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."}}