{"id":"W2967515408","doi":"10.1097/fch.0000000000000236","title":"Families in Context","year":2019,"lang":"en","type":"article","venue":"Family & Community Health","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kimberly-Clark (Canada)","funders":"","keywords":"Odds; Immigration; Food insecurity; Context (archaeology); Geography; Longitudinal data; Demography; Population; Environmental health; Food security; Psychology; Sociology; Medicine; Logistic regression","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003027143,0.0001993356,0.0005775335,0.0003310156,0.002024293,0.000009049086,0.0004981762,0.0002630984,0.0005080859],"category_scores_gemma":[0.0002063165,0.0002092804,0.00006759758,0.0005269906,0.00007714121,0.000208306,0.0003249907,0.003636746,0.003509044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007893328,"about_ca_system_score_gemma":0.0013708,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4478306,"about_ca_topic_score_gemma":0.4078165,"domain_scores_codex":[0.9935923,0.003963034,0.0009961807,0.0002226782,0.0002764784,0.0009493206],"domain_scores_gemma":[0.9967595,0.001420667,0.0003063562,0.001094444,0.0001321352,0.0002869029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005751491,0.0002433484,0.9112388,0.0009992934,0.000008203425,9.523849e-7,0.05159953,0.00002171645,0.00001532793,0.02353832,0.01049505,0.001781909],"study_design_scores_gemma":[0.001328343,0.000212203,0.7883773,0.0005474823,0.000001914187,3.716763e-7,0.1134722,0.0001542261,4.753819e-7,0.001109333,0.094648,0.0001481358],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9368576,0.000678385,0.00001694463,0.004116912,0.001207232,0.001628843,0.00008881327,0.000171177,0.0552341],"genre_scores_gemma":[0.9695496,0.0006246574,0.0002539445,0.02832313,0.00007265408,0.00008515346,0.0001101137,0.00002806959,0.0009526744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1228615,"threshold_uncertainty_score":0.9992749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2416353496682968,"score_gpt":0.4824594089506911,"score_spread":0.2408240592823943,"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."}}