Effects of Vessel Geometry, Fermenting Volume and Yeast Repitching on Fermenting Beer
Bibliographic record
Abstract
This paper statistically examines the effect of tank shape and size, fermenting volume and yeast pitching number on fermentation parameters routinely monitored in a series of industrial fermentations. With the fermenter tanks employed in this pilot study, little effect of tank shape existed between any of the parameters. The number of brews fermented or fermenting volume had a significant difference (p<0.05) on the apparent extract at 48 h, the final pH and the apparent degree of fermentation (ADF). Interestingly, the number of yeast repitchings (up to 13) did not show any effect on any of the parameters. We conclude, as have other studies, that the automatic practise of discarding the yeast crop after 10 fermentations (and the related expense of early yeast repropagation) could be questioned and is worthy of further study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".