North American Aboriginal people are
Bibliographic record
Abstract
experiencing an epidemic of type 2 dia-betes mellitus (T2DM) and its complica-tions.1-5 Both genetic and environmental factors have been implicated in this epi-demic, and the possible diabetogenic role of the intrauterine milieu has attracted increasing attention. The offspring of Pima women with T2DM and gestational diabetes (GDM) have increased rates of high birthweight (HBW), and a propensity to develop early age onset T2DM.6-8 North American Aboriginal women also have high rates of GDM,9-12 an observation that we even found in communities where the preva-lence of T2DM was still low.13 These reports raise the intriguing possibility that GDM may be one of the earliest manifesta-tions of carbohydrate intolerance in some Aboriginal populations, and an important contributing factor in the initiation and progression of the T2DM epidemic. A relationship between low birthweight (LBW) and T2DM has also been identi-fied,14-22 possibly due to impaired islet cell development caused by maternal/fetal mal-nutrition.23 Since Saskatchewan Aboriginal infants have experienced increased rates of LBW in the past,24,25 it is possible that LBW and its causes could also contribute to the Aboriginal T2DM epidemic. The purpose of this study was to examine the relationship between both HBW (>4000 g) and LBW (<2500 g) and the future develop-ment of T2DM among adult Registered Indians (RI) in Saskatchewan. An association between HBW and T2DM would suggest prenatal exposure to T2DM, GDM, or ges-tational impaired glucose tolerance (GIGT).26-29 An association between LBW and T2DM would suggest that poor mater-nal/fetal nutrition is relevant. If such relation-ships were observed, the findings could lead to prevention initiatives against intrauterine risk factors that contribute to the epidemic of T2DM in Aboriginal people.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".