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 (TSH), bologna size (diameter, D and height, H), surface heat transfer coefficients (hheat and hcool), product thermal diffusivity (αheat and αcool). Output variables were: product core temperature (Tc), core and volume‐average lethality (Pcm and Pvm) and cook (Cc and Cv) values as well as surface (Qs) and volume‐average (Qv) quality retention, total specific energy consumption (En) and energy efficiency (Ce). Multiple linear regression models were developed to predict Cc and Cv from five inputs and used to obtain acceptable deviation ranges.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".