doi:10.1155/2007/76271 Research Article Diabetic Retinopathy in Native and Nonnative Canadians
Bibliographic record
Abstract
High prevalence rates of type 2 diabetes are being observed in native Canadian communities. It is believed that native populations have a higher prevalence rate of vascular complications than nonnatives. The Southern Alberta Study of Diabetic Retinopathy (DR) examined the prevalence and incidence of DR and associated metabolic abnormalities in native and nonnative subjects. Prevalence rates of DR in type 2 diabetic native and nonnative subjects were identical, with a prevalence rate of 40%. Native subjects with retinopathy, however, tended to have more advanced changes of retinopathy compared to the nonnative subjects. Key factors such as A1c, blood pressure, duration of diabetes, and lipid values were not significantly different between the two cohorts. These data indicate that ethnicity does play a role in the development and severity of DR but potential risk factors that may affect the development of retinopathy are not significantly different between native and nonnative groups. Copyright © 2007 Stuart A. Ross et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.488 | 0.274 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".