Evaluating the Malting Quality of Hulless CDC Dawn, Acid-Dehusked Harrington, and Harrington Barley
Bibliographic record
Abstract
Hulless barley malt can result in significantly higher levels of extracts, lower freight costs, and reduced levels of polyphenols compared with conventional barley malt. The need for barley hull, which supplies no extract when brewing, has been reduced with the brewing industry's move toward new separation techniques, such as mash filters and centrifugation, versus the traditional lautering process where hulls are essential. Previous malting trials produced hulless malts with poor friability, possibly because of under modification or case hardening of the malt. To clarify the effect of hull absence on overall malt quality covered Harrington, hulless CDC Dawn, and acid-dehusked Harrington barley were malted under varying malting regimens. Hulless CDC Dawn malts produced significantly higher levels of malt extract than did covered Harrington malts, although, not as high as the 90% seen with acid-dehusked Harrington. CDC Dawn and covered Harrington malts had similar levels of enzymes and protein modification, but acid-dehusked Harrington still had higher levels of soluble protein that contributed to its higher levels of malt extract values. Freeze drying of green malt significantly improved friability values in hulless CDC Dawn and acid-dehusked Harrington, suggesting that regular kilning caused case hardening in the hulless and dehusked malts. It was concluded that high quality hulless malt could be produced provided appropriate malting conditions were used.
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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 | 0.001 | 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".