Bioconcentration of cedarwood oil constituents in rainbow trout
Bibliographic record
Abstract
Cedarwood oil is an essential oil used as a fragrance material and insect repellent. Its main constituents are sesquiterpenes which are potentially bioaccumulative according to the REACH screening criteria. Cedarwood oil is a complex mixture of hydrophobic and volatile organic chemicals. The volatility and limited water solubility of its constituents are a challenge for standard bioconcentration factor (BCF) test methods using aqueous exposure. We used an abbreviated dietary exposure in vivo testing protocol with internal benchmark substances as “internal standards” to derive the BCF of cedarwood oil constituents using rainbow trout (Oncorhynchus mykiss). Internal benchmarking proved to be a useful tool to control for inter-individual variability, enabling us to calculate the BCF for all major cedarwood oil constituents as a mixture. We found that the BCF of two out of six analysed cedarwood oil constituents exceed a BCF of 5000 and two others exceed a BCF of 2000 (90% confidence level) even though we found evidence for biotransformation for individual constituents. The results of this study indicate that more work is warranted to study the bioaccumulation of essential oils and highlights the utility of internal benchmarking in in vivo dietary exposure BCF tests to increase robustness and allow for the BCF measurement of complex mixtures.
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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) | 0.000 | 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 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".