Determining a relationship between licensing status and semi-quantitative risk score for BC dairy processing plants
Bibliographic record
Abstract
Background: Following the 2014 Gort’s Gouda Cheese Escherichia coli O157:H7 outbreak which resulted in one death and 28 illnesses, an examination of dairy processing plants (DPP) within British Columbia (BC) was undertaken. The intent of this examination was to efficiently allocate resources to ensure a lower likelihood of future outbreaks occurring in a BC DPP and to improve current knowledge regarding DPP practices. A risk-based approach to assessing inspection activities for DPPs was undertaken. As such, the purpose of the project was to create a semi-quantitative tool to assess inherent risk factors of DPPs, after which it would be used to determine appropriate inspection frequencies for these plants based on their risk scores. Finally, a comparison between provincially licensed and federally registered dairies was conducted in order to examine if there was a difference in risk between the two licensing statuses. Methods: A semi-quantitative approach was used to characterize responses to a survey (Shi, 2014) conducted by the BCCDC between August and December 2014. This survey was sent to all DPPs (n=54) operating in BC. Each survey question related to increasing information on conditions found in DPPs, after which a semi-quantitative assessment approach was used to assign a total risk inherent to each DPP due to the conditions found in the facility. The DPPs were then ranked against each other with respect to their risk scores in order to assess which facility was considered of higher risk. Facilities were grouped by their licensing status, provincially licensed or federally registered, and then compared against one another using a two variable t-test in NCSS 10. Semi-quantitative risk assessment was done using an Excel tool designed specifically for the present study. Results: Complete data was obtained for 85%(n=46) of DPPs, with an equal number of provincial and federal DPPs used in the evaluation. Dairies were ranked against one another with respect to their total risk score. A statistically significant difference (p=0.036) was found when comparing the inherent risk of provincial and federal DPPs, with federally registered dairies showing a lower total inherent risk score. Conclusion: The information obtained from this study provided the BCCDC with a standardized risk-based inspection approach. Ranking of DPPs with respect to their inherent risk also allows inspectors to gain better understanding of present day dairies and their high risk issues. This reassessment allows for the development of more efficient inspection schedules in order to effectively allocate inspection resources and to increase the ability for inspectors to capture and prevent risks which would lead to foodborne illnesses.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".