Silicone bakeware as a source of human exposure to cyclic siloxanes via inhalation and baked food consumption
Bibliographic record
Abstract
Silicone-based bakeware is widely used due to its heat resistance, flexibility, and non-stick properties. However, concerns have emerged regarding the potential migration and release of siloxanes from these products into food and indoor air during baking. This study evaluates human exposure to cyclic siloxanes via ingestion and inhalation, using silicone bakeware purchased on the Canadian market. Based on composition analysis, concentrations of total cyclic siloxanes (D4 - D16) in 25 bakeware products ranged from 680 µg/g to 4300 µg/g. Migration of siloxanes into food was assessed using Miglyol 812 N oil mixed with sand as a food simulant, while airborne emissions were measured at the same time during 60-minute baking sessions at 177 °C. The analytes were measured using GC/MS. The average concentration of the sum of D4 - D16 in baked food simulants was 105 µg/g. One-hour average concentrations of the sum of D4 - D16 in indoor air reached 646 µg/m³ , and declined rapidly post-baking. Migration into food simulants was influenced by bakeware type, surface area, and fat content. Repeated baking shows a steady decline in migration and emissions, suggesting depletion of siloxanes in the products over time. On a per-body-weight basis, daily intake estimates indicate that young children have the highest exposure in both ingestion of baked food and inhalation exposure of room air during baking. Heavy congeners (D7 - D16) contributed to the majority of daily intake of cyclic siloxanes from baked food. These findings highlight silicone bakeware as a source of cyclic siloxane exposure for the general population in Canada.
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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 | 0.000 | 0.000 |
| 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) | 0.003 | 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".