The Two Faces of <i>Lactobacillus kunkeei</i>: Wine Spoilage Agent and Bee Probiotic
Bibliographic record
Abstract
<h3>Summary</h3> <h3>Importance:</h3> <i>Lactobacillus kunkeei,</i> also known as the “ferocious lactobacilli”, causes fermentation arrest during wine production<sup>1</sup>. <i>L. kunkeei</i> co-evolved with honeybees and is an important probiotic for bee and hive health<sup>2</sup>. In the bee ecosystem, <i>L. kunkeei</i> is one of a suite of lactic acid bacteria that protect the bee and hive from pathogens as well as aid in preservation of sugar-rich hive resources. The protection of sugar-rich resources probably uses similar mechanisms to those inhibiting yeast during grape juice fermentation. <h3>Key Observations:</h3> The probiotic role of <i>L. kunkeei</i> Unique aspects of <i>L. kunkeei</i> metabolism enabling rapid growth in grape juice Proposed mechanisms of inhibition of yeast fermentation by <i>L. kunkeei</i> The environmental incentive for [<i>GAR</i><sup>+</sup>] prion induction by yeast in the presence of <i>L kunkeei</i> and fermentation arrest <h3>Impact and Significance:</h3> The essential role of <i>L. kunkeei</i> in prevention of bee colony collapse disorder limits the options available to winemakers for control of this pervasive spoilage agent. <i>L. kunkeei</i> can be controlled by sulfur dioxide (SO<sub>2</sub>) addition<sup>3</sup>. However, although this organism is sensitive to SO<sub>2</sub>, our data suggest that other microbes present in juice at the same time may reduce the effective concentration of SO<sub>2</sub>, thereby enabling growth of <i>L. kunkeei</i>. Clues from the mechanism of arrest of fermentation may help explain the role of <i>L. kunkeei</i> in bee health.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".