Expert Elicitation To Estimate the Feed Safety Impact of Criteria Included in the Canadian Food Inspection Agency Risk Assessment Model for Feed Mills
Bibliographic record
Abstract
ABSTRACT: The Canadian Food Inspection Agency is developing an Establishment-based Risk Assessment (ERA) model for commercial and on-farm mills involved in the manufacture, storage, packaging, labeling, or distribution of livestock feed (ERA-Feed Mill model). This model will help inform the allocation of inspection resources on the basis of feed safety risk, including animal health and food safety risk. In a previous study, 34 risk factors, grouped into inherent, mitigation, and compliance clusters, along with assessment criteria were selected. The objective of this current study was to estimate the relative risk (RR) of the 203 assessment criteria on the basis of the impact on feed safety to design an ERA-Feed Mill model algorithm. Furthermore, the intent of this study was to assess the maximum increase or decrease of risk obtained when multiple criteria belonging to a same cluster were identified in a specific feed mill. To do so, a two-round face-to-face expert elicitation was conducted with 28 Canadian feed experts. Results showed no significant association between respondent profiles (years of experience and work sector) and estimated RR. Uniformity of answers between experts improved between rounds. Criteria having the highest increase in risk (median RR ≥ 4) included the presence of materials prohibited to be fed to ruminants in a facility that produces ruminant feed, the presence of multiple livestock species on-site, and historical noncompliances related to the inspection of the feed mill's process control and end-product control programs. Risk mitigation criteria having the highest impact on decreasing the risk were the implementation of feed safety certifications, the use of dedicated manufacturing lines (prohibited materials or medications), and having a hazard sampling plan in place for finished feed. The median RR assigned to each criterion and cluster will be used to build an algorithm of the Canadian Food Inspection Agency's ERA-Feed Mill model.
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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 | 0.015 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".