Acid Diffusion in Solid Foods
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Foods acidified to pH levels below 4.5 can be thermally treated at lower temperatures under pasteurization conditions offering reduced thermal damage to product quality. Considering practical criterion, the main objective of this study was to investigate the proper acidification procedures of solid food particles immersed in liquid solutions. This was performed by testing a variety of factors, including particle type and size, temperature, and type and concentration of acids. Furthermore, the minimum acidification time of food particles was also determined. A standard model for mass transfer (e.g. Fick’s second law) was applied. Mass diffusion coefficients (DAB) were calculated based on experimental data. Average values of DAB were in the range of 10-8 to 10-10 m2/s and in agreement with existing literature data. Minimum acidification times varied depending on the type of acid, food, and treatment temperature, and ranged between 7 to 26 min. Meat particles were slowest to acidify, and acetic acid and tomato juice acidified by citric acid were the strongest acidifying agents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 | 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 it