Effects on Survival of Escherichia coli O157:H7 in Non-Intact Steaks of the Frequency of Turning Over Steaks During Grilling
Bibliographic record
Abstract
Beef steaks between 1 cm and 3 cm-thick were inoculated with Escherichia coli O157:H7 and/or temperature histories were collected at steak centres, at points initially below the central plane, and/or at points 1 cm or 2 cm from steak edges. The steaks were turned over once during grilling when temperatures at the centres reached 30°C or 50°C, or at specified times once, twice or several times during cooking to specified temperatures between 60and 71°C. When steaks were turned over at centre temperature of 30 or 50°C, some points in some steaks did not reach the temperatures specified for steak centres. When steaks turned over at 50°C were cooked to 60, 63 or 65°C, E. coli O157:H7 inoculated at ? 5 log cfu at each point survived at some points in some steaks at numbers ?3 log cfu. When steaks were turned over once during cooking to 71°C, E. coli O157:H7 survived at some points in some steaks turned over after ? 8 min. When steaks were turned over frequently, or twice at appropriate times during cooking to 63°C, no E. coli O157:H7 were recovered from any inoculated steak. Thus, cooking steaks to 71°C may sometimes have only relatively small effects on E. coli O157:H7 in steaks turned over once. However, turning steaks over twice or more during cooking to 63°C can ensure inactivation of large numbers of E. coli O157:H7 at all points in mechanically tenderized steaks.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".