Screening for Sulfate in Distillers Dried Grains and Solubles by FT–IR Spectroscopy
Bibliographic record
Abstract
Distillers Dried Grains and Solubles (DDGS) are an animal feed containing varying levels of sulfur. As ruminants are susceptible to high sulfur diets, sulfur content is of major interest to the parties involved. The variation in levels of sulfur in DDGS is mainly due to sulfate derived from the addition of sulfuric acid during the production. ATR/FT-IR spectroscopy was used to determine sulfate levels in 90 DDGS samples from various origins (Canada, China, EU, and U.S.A.). Specific absorption bands for sulfate at 615 and 1107 cm(-1) enabled the analysis of sulfate in the DDGS matrix. Besides direct quantification (using band at 615 cm(-1)), PLS regression was applied for the prediction of sulfate using FT-IR spectra and calibration with reference values analyzed by capillary electrophoresis. An extended calculation on the total sulfur estimated that 11% of the DDGS samples analyzed in this study featured sulfur contents higher than 0.80%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".