Impact of Artificially Induced Respiratory Deficient Yeast on Beer Flavor and Fermentation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Respiratory deficient cells or “petites” are the most common type of mutation found in brewing yeast. High levels of petites are known to contribute to unwanted flavors in beer along with yeast flocculation problems during fermentation. However, a minimal amount is known regarding the impact of petites when present at naturally occurring frequencies. Accordingly, this study investigated if petites, which are present at low frequencies, affect beer flavor and fermentation profiles. Laboratory [20 mL] fermentations were undertaken with yeast that contained a range of petite populations 3.7, 5.1, 8.7, and 10.8%. During fermentation, the yeast in suspension, wort density, and alcohol were monitored. At the end of the fermentation, the beer was analyzed for volatile flavor compounds. Correlations between petite levels and levels of vicinal diketones, acetate esters, and medium chain fatty acid (MCFA) ethyl esters existed. Higher alcohol levels were unchanged (propan-1-ol, 3-methyl butanol, 2-methyl butanol, and isobutanol) with increasing levels of petite concentrations. Similarly, the yeast in suspension behavior and the change in wort density attenuation between the control and petite enriched fermentations were not significantly different (P > 0.05). This study suggests that low concentrations of petites in the pitched yeast would not be detectable in the final product characteristics.
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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 it