A Novel Approach for a Functional Group to Predict Protein in Undigested Residue and Protein Digestibility by Mid-Infrared Spectroscopy
Bibliographic record
Abstract
To evaluate nutrient digestibility, we propose the novel approach of functional group digestibility (FGD). The FGD was based on the absorbance of specific Fourier transform infrared (FT-IR) peaks and the ratio of an inorganic indigestible marker in diet and digesta, without calibration. For application, samples of diet and digesta of wheat with predetermined crude protein (CP) digestibility were scanned on an FT-IR spectrometer equipped with a single-reflection attenuated total reflection (ATR) attachment. The FGD in the amide I region (1689-1631 cm (-1)) of digesta spectra was strongly related (R(2) = 0.99) with CP digestibility. The measured diet CP digestibility ranged from 60.4 to 87.8% with a standard error of prediction of 1.09%. In conclusion, instead of predictions based on calibrations, FGD can be calculated directly from spectra, provided the ratio of marker in diet and undigested residue is known, and then accurately predicts nutrient digestibility.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".