Characterizing chronic and acute health risks of residues of veterinary drugs in food: latest methodological developments by the joint FAO/WHO expert committee on food additives
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The risk assessment of residues of veterinary drugs in food is a field that continues to evolve. The toxicological end-points to be considered are becoming more nuanced and in light of growing concern about the development of antimicrobial resistance, detailed analysis of the antimicrobial activity of the residues of veterinary drugs in food is increasingly incorporated in the assessment. In recent years, the Joint FAO/WHO Expert Committee on Food Additives (JECFA) has refined its approaches to provide a more comprehensive and fit-for-purpose risk assessment. This publication describes in detail the consideration of acute and chronic effects, the estimation of acute and chronic dietary exposure, current approaches for including microbiological endpoints in the risk assessment, and JECFA's considerations for the potential effects of food processing on residues from veterinary drugs. JECFA now applies these approaches in the development of health-based guidance values (i.e. safe exposure levels) for residues of veterinary drugs. JECFA, thus, comprehensively addresses acute and chronic risks by using corresponding estimates for acute and chronic exposure and suitable correction for the limited bioavailability of bound residues by the Gallo-Torres model. On a case-by-case basis, JECFA also considers degradation products that occur from normal food processing of food containing veterinary drug residues. These approaches will continue to be refined to ensure the most scientifically sound basis for the establishment of health-based guidance values for veterinary drug residues.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 it