The promise and challenges of exposomics in child health research
Bibliographic record
Abstract
Childhood health is shaped by environmental exposures during sensitive windows of development. Longitudinal pregnancy and child cohorts have been designed to establish links between environmental exposures and child outcomes. The majority of studies focus on single exposures or groups of exposures and a specific health domain. The emerging field of exposomics aims to capture the totality of environmental exposures and through a multi-omics approach identify the biological response that mediates environmental triggers of health outcomes. Neighbourhood-level and individual-level environmental variables are measured by multidisciplinary methods to capture the exposome. Exposomics is in its infancy, but thus far a few multi-cohort projects have put this concept into practice and implemented a comprehensive measurement of the exposome during prenatal and early postnatal periods to determine associations with child health outcomes. Early findings have highlighted that children are exposed to a distinct collection of exposures in the womb and after birth and these development-specific exposures are associated with distinct molecular signatures. Exposomics has also proven useful in identifying the most important environmental drivers of child health and potential sources. Thus, this emerging field has the potential to inform public health interventions that promote healthy environments and identify the most vulnerable children. IMPACT: Discusses the emerging field of exposomics as a comprehensive approach to investigating environmental drivers of child health. Highlights current efforts to study the early life exposome and key findings. Identifies the value, challenges and limitations in exposomic research in child health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".