Physical Activity and Gestational Diabetes Mellitus
Bibliographic record
Abstract
Gestational diabetes mellitus (GDM) is defined as 'carbohydrate intolerance resulting in hyperglycemia of variable severity with onset or first recognition during pregnancy'. GDM is associated with several detrimental health consequences during pregnancy and delivery for both mother and baby. The largest public health impact of GDM is through its role on future diabetes in the mother and obesity and diabetes in the offspring. Physical activity (PA) is likely an effective intervention for prevention and treatment of GDM, given its known effectiveness in prevention and treatment of type 2 diabetes. Based on observational studies, PA initiated before and/or during pregnancy has a positive influence on maternal glucose and insulin metabolism and reduces the risk of GDM. However, although PA interventions have been reported to be effective at improving glycemic control in women who already developed GDM, prenatal PA interventions aimed at preventing GDM have shown modest effectiveness in increasing PA levels and thus were not effective in improving glucose/insulin metabolism or reducing GDM incidence. There is therefore a strong need to develop effective strategies for increasing PA levels, especially in women at high risk for GDM who are often obese and inactive. The optimal intervention for preventing or managing GDM is still unknown, and further studies are needed to determine the type, intensity, frequency and duration for the most successful PA intervention. Furthermore, the effects of PA on neonatal outcomes are not clear, and it is highly recommended that future studies examine more specific neonatal outcomes such as body composition.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".