Near Infrared Spectroscopy Using Short Wavelengths and Leave-One-Cow-Out Cross-Validation for Quantification of Somatic Cells in Milk
Why this work is in the frame
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Bibliographic record
Abstract
A short wavelength near infrared (NIR) analysis method for somatic cell count (SCC) determination in unhomogenised raw milk was developed. NIR spectra (700–1100nm) of unhomogenised milk samples from 14 cows during days 7 to 36 of their lactation were measured for two consecutive years. Measurements from animals with different physiological conditions (healthy and mastitic)were included. A “leave-one-cow-out” cross-validation partial least square (PLS) regression model for SCC in the raw milk was developed. Good correlation ( R 2 =0.76) was observed between estimated and reference SCC levels in milk samples when the differential spectra and SCC reference values were used for developing the PLS model. The NIR estimation achieved a standard error of 0.3 LogSCC. The results were well within the range needed for real-time monitoring of milk on a daily basis. Thus, the NIR method may prove to be a valuable tool for monitoring somatic cells in routine milk samples analysed for dairy cow health management.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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