Factors that influence excessive gestational weight gain: moving beyond assessment and counselling
Bibliographic record
Abstract
One in four Canadian adults is obese, and more women are entering pregnancy with a higher body mass index (BMI) than in the past. Pregnant women who are overweight or obese have a higher risk of pregnancy-related complications than women of normal weight. Gestational weight gain (GWG) is also associated with childhood obesity. Although the factors influencing weight gain during pregnancy are multifaceted, little is known about the social inequality of GWG. This review will address some of the socioeconomic factors and maternal characteristics influencing weight gain and the impact that excessive GWG has on health outcomes such as post-partum weight retention. The effects of an overweight or obese pre-pregnancy BMI on GWG and neonatal outcomes will also be addressed. The timing of weight gain is also important, as recommendations now include trimester-specific guidelines. While not conclusive, preliminary evidence suggests that excessive weight gain during the first trimester is most detrimental.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".