FEMA GRAS assessment of derivatives of basil, nutmeg, parsley, tarragon and related allylalkoxybenzene-containing natural flavor complexes
Bibliographic record
Abstract
In 2015, the Expert Panel of the Flavor and Extract Manufacturers Association (FEMA) initiated a program for the re-evaluation of the safety of over 250 natural flavor complexes (NFCs) used as flavoring ingredients in food. In this publication, tenth in the series, NFCs containing a high percentage of at least one naturally occurring allylalkoxybenzene constituent with a suspected concern for genotoxicity and/or carcinogenicity are evaluated. In a related paper, ninth in the series, NFCs containing anethole and/or eugenol and relatively low percentages of these allylalkoxybenzenes are evaluated. The Panel applies the threshold of toxicological concern (TTC) concept and evaluates relevant toxicology data on the NFCs and their respective constituent congeneric groups. For NFCs containing allylalkoxybenzene constituent(s), the estimated intake of the constituent is compared to the TTC for compounds with structural alerts for genotoxicity and when exceeded, a margin of exposure (MOE) is calculated. BMDL10 values are derived from benchmark dose analyses using Bayesian model averaging for safrole, estragole and methyl eugenol using EPA's BMDS software version 3.2. BMDL10 values for myristicin, elemicin and parsley apiole were estimated by read-across using relative potency factors. Margins of safety for each constituent congeneric group and MOEs for each allylalkoxybenzene constituent for each NFC were determined that indicate no safety concern. The scope of the safety evaluation contained herein does not include added use in dietary supplements or any products other than food. Ten NFCs, derived from basil, estragon (tarragon), mace, nutmeg, parsley and Canadian snakeroot were determined or affirmed as generally recognized as safe (GRAS) under their conditions of intended use as flavor ingredients based on an evaluation of each NFC and the constituents and congeneric groups therein.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".