Volatility of Fragrance Chemicals: Patch Testing Implications
Bibliographic record
Abstract
BACKGROUND: Diagnostic and predictive patch testing to determine contact allergy due to fragrance materials requires applying a fixed dose of material to the skin. This dose can be affected by the volatile nature of fragrances; little data exist on how the loss of fragrance dose due to volatility affects patch testing. OBJECTIVE: (1) To evaluate pH dependence and evaporation rates of two fragrance chemicals, geraniol, citronellol, and a common fragrance solvent, diethyl phthalate (DEP) and (2) Assess implications for predictive patch-testing methods for fragrances. METHOD: pH analysis of each material at 1% for three values (4.0, 5.0, 7.0) was done over 40 hours. Volatility experiments for each material, nonradiolabeled and radiolabeled, were conducted over a 24-hour period, taking readings at six time points (5 minutes, 15 minutes, 40 minutes, 1 hour, 3 hours, and 24 hours). RESULTS: Evaporation rates were not sensitive to pH shifts from 4.0 to 7.0. Evaporation rates for nonradiolabeled materials were low: after 24 hours, geraniol lost 8.9%, citronellol 27.0% and DEP 14.5%. The volatility data for radiolabeled materials demonstrated that geraniol loses up to 39% of its dose, citronellol loses up to 26%, and DEP up to 14% within 40 minutes. CONCLUSION: The tendency of fragrance materials to evaporate can impact the dose being applied to the patch and therefore the result of the patch and ultimately the decision-making process regarding that fragrance material's safety. These data, developed with DEP, utilized in a predictive sensitization assay cannot be generalized.
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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 | 0.000 | 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) | 0.000 | 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".