Progress in understanding the paleness of meat with a low pH: keynote address
Bibliographic record
Abstract
Meat with a low pH is generally paler than at a high pH. Paleness related to pH is caused by light scattering. Myofibrils are a primary cause of pH-related light scattering in meat, but light scattering is also related inversely to sarcomere length. We do not yet know the relative importance of surface reflectance from myofibrils vs. refraction through the depth of myofibrils. Precipitation of sarcoplasmic proteins is added to myofibrillar scattering when pH is extremely low, or when pH reaches low levels while meat is still hot. Scattering tends to decrease the length of the light path through meat. This reduces selective absorbance by myoglobin. Thus, the colour of meat is more conspicuous when pH is high. Recent experiments show a direct contribution from mitochondria to the optical properties of meat. Progress in this subject helps explain meat colour and may help us improve optical methods for predicting meat quality on-line. South African Journal of Animal Science Supp 2 2004:1-7
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".