Work Activity in Pregnancy, Preventive Measures, and the Risk of Delivering a Small-for-Gestational-Age Infant
Bibliographic record
Abstract
OBJECTIVES: We undertook a case-control study to evaluate whether some occupational conditions during pregnancy increase the risk of delivering a small-for-gestational-age (SGA) infant and whether taking measures to eliminate these conditions decreases that risk. METHODS: The 1536 cases and 4441 controls were selected from 43898 women who had single live births between January 1997 and March 1999 in Québec, Canada. The women were interviewed by telephone after delivery. RESULTS: The risk of having an SGA infant increased with an irregular or shift-work schedule alone and with a cumulative index of the following occupational conditions: night hours, irregular or shift-work schedule, standing, lifting loads, noise, and high psychological demand combined with low social support. When the conditions were not eliminated, the risk increased with the number of conditions (P(trend) =.004; odds ratios=1.00, 1.08, 1.28, 1.43, and 2.29 for 0, 1, 2, 3, and 4-6 conditions, respectively). Elimination of the conditions before 24 weeks of pregnancy brought the risks close to those of unexposed women. CONCLUSIONS: Certain occupational conditions experienced by pregnant women can increase their risk of having an SGA infant, but preventive measures can reduce the risk.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".