Bibliographic record
Abstract
Purpose: This study aimed to review recent findings from birth cohort studies on maternal and child environmental health. Methods: Birth cohort studies regarding environmental health outcomes for mothers and their children were investigated through a systematic review. A literature search was conducted in PubMed, CINAHL, the Cochrane Library, Embase, and RISS to identify published studies using the keywords using a combination of the following keywords: maternal exposure, environmental ex posure, health, cohort, and birth cohort. Articles were searched and a quality appraisal using the Newcastle-Ottawa Scale for cohort studies was done. Results: A review of the 14 selected studies revealed that prenatal and early life exposure to environ mental pollutants had negative impacts on physical, cognitive, and behavioral development among mothers and children up to 12 years later. Environmental pollutants included endocrine disruptors, air pollution (e.g., particulate matter), and heavy metals. Conclusion: This systematic review demonstrated that exposure to environmental pollutants nega tively influences maternal and children’s environmental health outcomes from pregnancy to the ear ly years of life. Therefore, maternal health care professionals should take steps to reduce mothers’ and children’s exposure to environmental pollutants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".