Sous vide salmon pasteurization temperature
Bibliographic record
Abstract
Objectives: Cooking foods to a specific temperature and temperature control are often very difficult due to the frequent fluctuation of heat during the traditional dry heat (oven) cooking process. “Sous vide” cooking of vacuum-packaged foods immersed in water provides constant and controllable time and temperature measurements throughout the process. Some sous vide style foods are cooked at temperatures that are lower than 60oC for short periods of time. This presents a recognizable food safety concern including the survival of harmful bacteria as well as conditions that do not achieve pathogen reduction during either the sous vide cooking or finishing (searing) process. This research project investigated the time and temperature relationship for sous vide salmon in order to examine if pasteurization temperature was achieved if an additional searing step was performed. Methods: Temperature values were measured using data-loggers (SmartButton) for 30 samples of vacuum-packed salmon and cooked sous vide inside a circulating water bath at 50oC for 20 minutes. A one sample one tailed t-test was conducted to assess whether the internal temperature of salmon reached instantaneous pasteurization temperature of 70oC after a final searing step was performed at 220oC for 45 seconds. Results: Five out of the 30 (16.7%) salmon samples achieved 70oC after the final searing step. Statistical analyses were statistically significant, and the null hypothesis (Ho: measured internal temperature of salmon ≥ target temperature) was rejected with 100% power and a p-value of 0.00. Conclusion: These results indicate that salmon cooked sous vide style under 50oC for 20 minutes with a final searing step of 220oC for 45 seconds will likely not achieve pasteurization providing adequate pathogen reduction according to guidelines set out by BCCDC. For sous vide style cooked salmon cooked at lower temperatures for short periods, freezing for control of parasite hazards is recommended.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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".