Modelling of cooking‐cooling processes for meat and poultry products
Bibliographic record
Abstract
Summary Traditional cooking‐cooling of processed meat and poultry products is industrially carried out in smokehouses or autoclaves. A mathematical model was developed to simulate these operations. Equations, describing heat transfer and thermal destruction of micro‐organisms and quality characteristics, were solved numerically. The model was validated experimentally for heat transfer and energy consumption and was used to perform a sensitivity analysis. Input variables were: process time (PT), smokehouse temperature ( T SH ), bologna size (diameter, D and height, H ), surface heat transfer coefficients ( h heat and h cool ), product thermal diffusivity ( α heat and α cool ). Output variables were: product core temperature ( T c ), core and volume‐average lethality ( P cm and P vm ) and cook ( C c and C v ) values as well as surface ( Q s ) and volume‐average ( Q v ) quality retention, total specific energy consumption (En) and energy efficiency (Ce). Multiple linear regression models were developed to predict C c and C v from five inputs and used to obtain acceptable deviation ranges.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".