Metabolic characteristics of proteins and biomolecular spectroscopic profiles in different batches of feedstock (wheat) and their co-products (wheat distillers dried grains with solubles) from the same bioethanol processing plant
Bibliographic record
Abstract
The objectives of this study were (1) to reveal the metabolic characteristics of proteins in different batches of feedstock (wheat) for bioethanol production and their co-products (wheat distillers dried grains with solubles, wDDGS) from the same bioethanol processing plant, and (2) to characterize biomolecular spectral profile associated with nutrient digestion in the rumen and intestine of dairy cattle. The metabolic characteristics of proteins were determined using the DVE/OEB system (where DVE=total truly absorbed protein supply, and OEB=degraded balance of protein) based on chemical profiles and rumen and intestinal digestion data from dairy cattle. The biomolecular spectral characteristics were investigated by using the molecular spectroscopy technique attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FT/IR). Multivariate molecular spectral analyses-agglomerative hierarchical cluster analysis (AHCA), and principal component analysis (PCA)-were conducted to identify the spectral differences in biomolecular inherent structure among the wheat and wDDGS batches. The results showed that (1) the metabolic characteristics of proteins in the wheat and wDDGS from the same bioethanol processing plant were significantly affected by batch, with total truly absorbed protein supply (DVE value) ranging from 101 to 116 g/kg of dry matter (DM) in wheat and from 153 to 182 g/kg of DM in wDDGS; (2) the degraded balance of protein (OEB value) in the wDDGS (but not the wheat) from the same bioethanol processing plant was significantly affected by batch, with the OEB value ranging from -19 to -26 g/kg of DM in the wheat and from 145 to 181 g/kg of DM in the wDDGS; and (3) the biomolecular spectral analyses with AHCA and PCA revealed biomolecular spectral profiles and differences among the wheat and wDDGS samples.
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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 | 0.001 |
| 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) | 0.000 | 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 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".