Effects of condensed distillers solubles and drying temperature on the physico-chemical characteristics of laboratory-prepared wheat distillers grain with solubles
Bibliographic record
Abstract
Samples of wheat distillers grain with solubles were prepared at 15%, 30%, and 45% condensed distillers solubles (CDS) and dried under 40C, 80C, and 120C to examine the effects of CDS level and drying temperature on their chemical, physical, flow, compression, thermal, and frictional properties. As CDS level increased, protein and ash contents increased while fat and fiber contents decreased. Fat and acid detergent fiber contents were also markedly affected by drying temperature. While CDS level, drying temperature, and their interaction significantly affected a number of the physical properties, results suggest that CDS level had a stronger influence. Samples with high CDS level, for example, were significantly finer, denser, less flowable, and less dispersible than those with lower CDS. These samples also had significantly higher thermal diffusivity and coefficient of internal friction and produced pellets with higher failure stresses than those with lower CDS. Their pellet density increased with CDS level and was also significantly affected by drying temperature. Further, the samples were classified as fairly flowable and floodable and their compression characteristics were adequately described by the Kawakita-Ludde model.
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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".