Calorimetry and Pressure-shift Freezing of Different Food Products
Why this work is in the frame
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Bibliographic record
Abstract
Rapid depressurisation can create uniform, small and abundant ice nucleation during pressure-shift freezing (PSF) which can then protect the frozen food structure from cell damage. The amount of depressurisation-formed ice was evaluated using a high-pressure calorimeter for different food products (tylose, potato, salmon, pork and water). Experiments were conducted at an initial pressure of 62, 82, 112, 156, 180 and 196MPa, at temperatures set at −5, −7, −10, −15, −18 and −20°C, respectively (slightly above the phase diagram of water-ice I). Calorimetric thermograms recorded during PSF tests were used for computing the quantity of ice formed based on heat balance. A polynomial relationship was established for each product to compute the depressurisation-formed ice ratio as a function of the initial pressure applied. This model accurately predicted the maximum ice ratio for PSF at a given pressure (0.1 to 210MPa) or the minimum ice ratio for PSF at a given temperature (−22 to 0°C). Moisture content was the major factor affecting the sample-mass based (SMB) ice ratio with higher moisture yielding a higher SMB ice ratio. A general relationship between water-mass based (WMB) ice ratio ( R'ice-water) and initial pressure was found from the pooled data from all tested products: R'ice-water 0.114 P+0.00022 P 2 (R 2 0.94, n 47) which agreed well with relevant literature values for pure water.
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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 | 0.001 |
| 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