Malting Characteristics of Three Canadian Hulless Barley Varieties, CDC Freedom, CDC McGwire, and CDC Gainer
Bibliographic record
Abstract
The malting quality of three Canadian hulless barley varieties, CDC Freedom, CDC McGwire, and CDC Gainer was investigated with micro- and pilot malting equipment. Results indicated that all three varieties could be micromalted successfully to produce malt with impressively high malt extract levels, 3–5% higher than a covered malting barley control, AC Metcalfe. However, under deep-bed malting conditions that simulated commercial malting conditions, some problems were observed. The lack of protection by a husk in the hulless barleys resulted in excessive acrospire damage during turning and handling that stopped growth. This resulted in restricted modification, high β-glucan levels, and reduced levels of enzymes. It is possible that the damage to acrospires could be minimized by adjusting the frequency and speed of turning during germination. Results also indicated that the quality of hulless malt, especially malt friability and α-amylase levels, were sensitive to harsh kilning conditions, although quality was less affected by the milder kilning conditions of the more commercial-like, deep-bed malting plant that offered support to the commercial malting of hulless barley. Among the three hulless varieties, CDC McGwire malt had more balanced quality with the highest friability and the lowest level of β-glucan content.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".