Bibliographic record
Abstract
Smoking during pregnancy is a serious public healthproblem, with adverse effects for both mother andbaby.1–4 It is estimated that 25%–40 % of women smokers try to stop smoking on their own upon learning that they are pregnant,5 yet little information is available at a population level on smoking patterns during pregnancy. In this report we describe the prevalence of smoking among pregnant women in Nova Scotia in 1997. Information concerning all hospital births in Nova Sco-tia in 1997 that was routinely collected by the Nova Scotia Atlee Perinatal Database was used in our study. Standard-ized forms were completed prospectively by medical per-sonnel at prenatal visits, during labour and delivery, and in the postpartum period up to the time of discharge. Infor-mation on smoking included self-reported smoking status and the mean number of cigarettes smoked per day. A total of 9808 women in Nova Scotia delivered a live infant in hospital in 1997. The figures reported here con-cern 8528 women whose smoking status before their preg-nancy is known. The overall rate of smoking before preg-nancy (n = 2822) was 33.1 % (95 % confidence interval [95 % CI] 32.1%–34.1%). Fig. 1 presents the changes in smoking status that oc-curred from before pregnancy to the first prenatal visit, and then to the time of admission for delivery. Of the 2822 women who were smokers before their pregnancy, 1973 (69.9%) remained smokers throughout their pregnancy (95 % CI 68.2%–71.6%). Another 8.4 % (237/2822) were The natural history of smoking during pregnancy among women in Nova Scotia
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.379 | 0.210 |
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".