{"id":"W2031993340","doi":"10.1139/h10-002","title":"Nutrition inequities in Canada","year":2010,"lang":"en","type":"article","venue":"Applied Physiology Nutrition and Metabolism","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research; Health Canada","keywords":"Socioeconomic status; Environmental health; Micronutrient; Psychological intervention; Educational attainment; Household income; Life expectancy; Public health; Gerontology; Consumption (sociology); Supplemental Nutrition Assistance Program; Medicine; Geography; Population; Food security; Economics; Food insecurity; Agriculture; Sociology; Economic growth","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.0006626797,0.0002273436,0.0004622987,0.002673476,0.007754671,0.002052048,0.0007387981,0.0004123311,0.006495303],"category_scores_gemma":[0.002330439,0.0001745432,0.0004919153,0.006681907,0.000941073,0.000529371,0.00191734,0.0008045477,0.0001967619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05805337,"about_ca_system_score_gemma":0.09160978,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9979127,"about_ca_topic_score_gemma":0.9988871,"domain_scores_codex":[0.9986404,0.0000669105,0.00005215479,0.0001416416,0.0004310412,0.000667871],"domain_scores_gemma":[0.9984047,0.00007885062,0.0001804002,0.00004005773,0.0006449895,0.0006510623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001859774,0.000116318,0.7945949,0.0003790485,0.0002012223,0.0006918188,0.006361276,0.0007715801,0.000437274,0.01973657,0.03321958,0.1433043],"study_design_scores_gemma":[0.00002020137,0.00002216181,0.9668027,0.0002190438,0.00004977228,0.000175097,0.003665491,0.0005017832,0.00007621497,0.002064248,0.02636324,0.00003997756],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8780095,0.01169826,0.000548713,0.01664481,0.0002001612,0.0001411326,0.01624967,0.00008335037,0.07642437],"genre_scores_gemma":[0.9898356,0.00309217,0.0004358421,0.001189514,0.00001819917,0.00002988199,0.001639317,0.00001125255,0.00374835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05805337,"threshold_uncertainty_score":0.4212087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05562694571868878,"score_gpt":0.3597611412235683,"score_spread":0.3041341955048796,"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."}}