Modeling Alkaline Phosphatase Inactivation in Bovine Milk During High-Temperature Short-Time Pasteurization
Bibliographic record
Abstract
Alkaline phosphatase (AP) is used as the indicator enzyme for proper pasteurization of bovine milk. Predictive modeling of AP inactivation during high-temperature short-time (HTST) pasteurization would support regulations; thus ensuring the safety of heat treated milk. Activation energy (Ea) of AP in milk was measured experimentally using the capillary tube method, and Ea was found to be 429252 J/mol. The Ea was used to develop a nonlinear model to describe the thermal inactivation of milk in a small-scale HTST pasteurizer with a plate heat exchanger. Integrated pasteurization effect (PE) was obtained at different holding temperatures (62–72°C) and holding times (3–25 s), by converting times at different temperatures in various sections of the pasteurizer to the equivalent time at the reference temperature (72°C). A nonlinear function was developed to relate the log(% residual AP activity) to PE. The r 2 varied from 0.7488 to 0.8311. The validation trial indicated that the model could predict AP activity accurately for the% residual AP activity >1%.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".