MétaCan
Menu
Back to cohort
Record W2313167446 · doi:10.1177/1010539514551200

Rural–Urban Differences in the Prevalence of Chronic Disease in Northeast China

2014· article· en· W2313167446 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAsia Pacific Journal of Public Health · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsUniversity of Saskatchewan
FundersChina Scholarship CouncilUniversity of Saskatchewan
KeywordsMedicineChronic bronchitisDiseaseEnvironmental healthRural areaChronic diseasePublic healthLogistic regressionChinaInternal medicineGeographyPathology

Abstract

fetched live from OpenAlex

Rural-urban differences in the prevalence of chronic diseases in the adult population of northeast China are examined. The Jilin Provincial Chronic Disease Survey used personal interviews and physical measures to research the presence of a range of chronic diseases among a large sample of rural and urban provincial residents aged 18 to 79 years (N = 21 435). Logistic regression analyses were used. After adjusting for age and gender, rural residents had higher prevalence of hypertension, chronic ischemic heart disease, cerebrovascular disease, chronic low back pain, arthritis, chronic gastroenteritis/peptic ulcer, chronic cholecystitis/gallstones, and chronic lower respiratory disease. Low education, low income, and smoking increased the risk of chronic diseases in rural areas. Reducing rural-urban differences in chronic disease presents a formidable public health challenge for China. The solution requires focusing attention on issues endemic to rural areas such as poverty, lack of chronic disease knowledge, and the inequality in access to primary care.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.345

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.256
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it