Fiber-optic spectrophotometry of streaking in pork loins injected with sodium chloride and tripolyphosphate
Bibliographic record
Abstract
Enhanced pork produced by needle injection of sodium chloride and tripolyphosphate loses its visual appeal if it has pale streaks on a dark background. Reflectance (R) spectrophotometry was used to test the hypothesis needle injection causes pale streaks by elution of myoglobin. Pale streaks in commercial pork loins (n = 10) had higher R than dark streaks (P < 0.01 from 350 to 590 nm) but differences between pale and dark streaks were almost a linear function of wavelength (r = -0.92, P < 0.0005) with no evidence of myoglobin elution. Using the same apparatus, myoglobin elution was detected in small disks of pork perfused experimentally for 1 h (n = 31 spectra, 2 min apart), comparing water (control, n = 5 disks) with commercial injection solution (n = 5 disks). Myoglobin elution by water increased R (P < 0.005) from 350 to 650 nm with a maximum effect at 440 nm, close to the Soret absorbance band for myoglobin. Perfusion of disks with commercial injection solution produced a complex result with the myoglobin elution pattern (increased R peaking at 440 nm) superimposed on an overall decrease in R, probably from sodium salts dissolving myofibrillar proteins (P < 0.005 from 350 to 360 nm, from 400 to 420 nm, at 440 nm, and from 460 to 540 nm). Thus, there was no support for the initial working hypothesis pale streaks are caused by myoglobin elution because the myoglobin elution pattern (increased R peaking at 440 nm) was absent in commercial pork loins. If perfusing small disks of pork is a valid experimental model of what happens in needle-injected loins, transient pale streaks might be muscle fasciculi not yet reached by injected solution. Key words: Enhanced pork, streaking, needle injection
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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 | 0.000 |
| 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) | 0.001 | 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".