Vulnerable Populations and Personal Care Products: The Role of Estimating Exposure to Products Used Primarily by Infants and Young Children
Bibliographic record
Abstract
Infants and young children are often key sub-populations of interest when assessing exposure to chemicals for human health risk assessments. As developing humans, children have distinct behavioral characteristics and potential routes of exposure that contribute to the unique differences in their susceptibility to environmental exposures. These include, but are not limited to, increased time on the floor, dust ingestion and mouthing of objects. In addition, there are many products that are marketed for use specifically by infants and children, for example diaper cream and baby wipes. No regulatory guidance specific to cosmetics and personal care products with a focus on infants and young children is currently available. This poster will discuss the unique considerations that go into estimating exposures to products used primarily on/by infants and young children. An overview of exposure factors compiled over the last 15 years, as well as the challenges and uncertainties associated with these approaches to risk assessment will be discussed. A few case studies will also be presented highlighting the use of these considerations to quantify chemical exposure in this subpopulation for regulatory risk assessment. These case studies will include substance groupings under the Government of Canada’s Chemicals Management Plan such as phthalates, as well as other select substances.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".