Complications of Type 2 Diabetes Among Aboriginal Canadians
Bibliographic record
Abstract
Despite a dramatically increasing burden of type 2 diabetes in Aboriginal Canadian communities (1–5), relatively little information is available regarding the prevalence of, and risk factors for, the complications of type 2 diabetes in this population (6). Although previous studies have documented micro- and macrovascular disease in Aboriginal Canadians with diabetes, the majority of these reports have relied heavily on hospital records, chart reviews, and disease registries (6). These approaches may underestimate the magnitude of the complications burden because only those with the severest disease are included, and standardized methods are infrequently used to document complications. The objective of the present research project was to systematically determine, using validated methods, the prevalence of micro- and macrovascular complications among Aboriginal Canadians who have type 2 diabetes and to identify risk factors that are associated with these conditions. The Sandy Lake Diabetes Complications Study has been presented in detail previously (6). Briefly, all community members known to have type 2 diabetes were invited to participate; 189 of 250 (76%) eligible subjects were enrolled, although the sample size varies given time-limited access to certain equipment. Participants were older than nonparticipants and more likely to be male but did not differ in diabetes treatment. Signed informed consent was obtained from all participants, and the study was approved by the Sandy Lake First Nation Band Council and the Mount Sinai Hospital Ethics Review Committee. We used validated measures to assess retinopathy, neuropathy, nephropathy, and cardiovascular disease risk factors, as described previously (6). Digital fundus photography was performed using a nonmydriatic retinal camera, with …
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".