O1B.1 Modeling infertility in a cohort of canadian tradeswomen
Bibliographic record
Abstract
Introduction With few female occupational cohorts, little is known about the contribution of work exposures to female infertility. Methods A cohort of 888 tradeswomen across Canada was established (450 welders and 438 in the electrical trades) to examine effects on the fetus, with investigation of infertility a secondary objective. Women completed an extensive questionnaire at recruitment and follow-up questionnaires every six-months for up to 5 years. At each contact she was asked about attempts to get pregnant and barriers to conception. Fertility issues were identified both by self-report of failure to conceive for ≥12 months and as the likelihood of conceiving in any month at risk. Determinants of infertility were examined in a Cox regression with time dependent covariates. Employment factors examined in each month were paid work, trade work and cumulative months in trade. Maternal age, prior conceptions, smoking, use of alcohol and BMI were examined as confounders. Results 96 periods of infertility ≥12 months were reported among 38 women from welding and 52 from electrical trades giving the risk of infertility for welders relative to electricians of 0.71 (95%CI 0.48–1.06). Total person months at risk (excluding months with no sex, pregnancy, surgical sterility or menopause) were 12 696 for welders and 13 313 for electricians. Likelihood of conceiving in any month at risk was significantly reduced with use of better contraception, drinking >7 units of alcohol, increasing age, number of previous pregnancies and, for welders, smoking >10 cigarettes/day. No effect of either current or cumulative work in trade was evident having adjusted for confounding. HR for working as a welder was −0.07 95% CI −0.49–0.35. Conclusions Female infertility presents challenges as an outcome in occupational epidemiology, but data can be structured to allow for time at risk. Analysis to date has demonstrated no important effect of exposure to welding.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".