{"id":"W3083828836","doi":"10.1371/journal.pone.0238577","title":"State-level income inequality and the odds for meeting fruit and vegetable recommendations among US adults","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Queen's University","funders":"Canada Excellence Research Chairs, Government of Canada; Canada Research Chairs; Government of Canada; University of Nevada, Reno","keywords":"Odds; Inequality; Odds ratio; State (computer science); Economic inequality; Demography; Environmental health; Medicine; Logistic regression; Mathematics; Sociology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005583661,0.0001119512,0.000140938,0.0004051035,0.000206782,0.0003590944,0.000200085,0.0002224397,0.00222028],"category_scores_gemma":[0.002726109,0.0001131562,0.0003328092,0.0005809441,0.0001653042,0.0003058404,0.0003668175,0.0004509322,0.0001460751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002493656,"about_ca_system_score_gemma":0.0002320538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01816076,"about_ca_topic_score_gemma":0.01656883,"domain_scores_codex":[0.9997813,0.00006004488,0.000024297,0.00005529778,0.00003736415,0.00004158655],"domain_scores_gemma":[0.9985914,0.0002976927,0.0007202714,0.00007827306,0.0001444485,0.0001679122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003144575,0.000016898,0.9988164,0.000004746929,0.0000370466,0.000009255965,0.00003627501,0.00006573902,0.00002367815,0.0000318665,0.0001235295,0.0008031896],"study_design_scores_gemma":[0.000002487135,0.0000161588,0.9993832,0.00000681354,0.00001607023,0.0000227886,0.0000704999,0.0003202704,0.00001394825,0.00004959369,0.00009658854,0.000001435606],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984277,0.0002029633,0.00008744692,0.0001528495,0.000004215286,0.000003850766,0.0005898832,0.000003815792,0.0005272733],"genre_scores_gemma":[0.9994628,0.0000628198,0.0000411543,0.00001548458,0.000003964288,0.000003168924,0.0003443223,7.745102e-7,0.00006565791],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01816076,"threshold_uncertainty_score":0.0361101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1330610297737143,"score_gpt":0.3258437252444942,"score_spread":0.1927826954707799,"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."}}