The Role of Healthcare Professionals in Environmental Health and Fertility Decision-Making
Bibliographic record
Abstract
There is increasing evidence that raises specific concerns about prenatal exposures to toxic substances which makes it necessary to consider everyday exposures to industrial chemicals and toxic substances in consumer products, including endocrine disrupting chemicals. Pregnant women have measurable levels of numerous toxic substances from exposures in their everyday environments, including those which are associated with adverse developmental and reproductive health outcomes. As a result, environmental contexts have begun to influence the decisions women make related to fertility, as well as the formal guidelines and advice provided by healthcare professionals. This article provides an overview of the potential role for obstetricians and gynecologists in educating their patients about the role of toxic substances in fertility decision-making and pregnancy. It explores the emerging guidelines and recommendations from professional organizations and problematizes the limitations of these approaches.
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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 | 0.052 | 0.110 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.008 | 0.008 |
| 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".