A global human health risk assessment for Decamethylcyclopentasiloxane (D5)
Bibliographic record
Abstract
Decamethylcyclopentasiloxane (D5) is a low-molecular-weight cyclic siloxane used primarily as an intermediate in the production of several widely-used industrial and consumer products and intentionally added to consumer products, personal products and some dry cleaning solvents. The global use requires consideration of consumer use information and risk assessment requirements from various sources and authoritative bodies. A global "harmonized" risk assessment was conducted to meet requirements for substance-specific risk assessments conducted by regulatory agencies such as USEPA's Integrated Risk Information System (IRIS), Health Canada and various independent scientific committees of the European Commission, as well as provide guidance for chemical safety assessments under REACH in Europe, and other relevant authoritative bodies. This risk assessment incorporates global exposure information combined with a Monte Carlo analysis to determine the most significant routes of exposure, utilization of a multi-species, multi-route physiologically based pharmacokinetic (PBPK) model to estimate internal dose metrics, benchmark modeling to determine a point of departure (POD), and a margin of safety (MOS) evaluation to compare the estimates of intake with the POD. Because of the specific pharmacokinetic behaviors of D5 including high lipophilicity, high volatility with low blood-to-air partition coefficients and extensive metabolic clearance that regulate tissue dose after exposure, the use of a PBPK model was essential to provide a comparison of a dose metric that reflects these processes. The characterization of the potential for adverse effects after exposure to D5 using a MOS approach based on an internal dose metric removes the subjective application of uncertainty factors that may be applied across various regulatory agencies and allows examination of the differences between internal dose metrics associated with exposure and those associated with adverse effects.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".