Sequence-based analysis of the microbial composition of water kefir from multiple sources
Bibliographic record
Abstract
Water kefir is a water-sucrose-based beverage, fermented by a symbiosis of bacteria and yeast to produce a final product that is lightly carbonated, acidic and that has a low alcohol percentage. The microorganisms present in water kefir are introduced via water kefir grains, which consist of a polysaccharide matrix in which the microorganisms are embedded. We aimed to provide a comprehensive sequencing-based analysis of the bacterial population of water kefir beverages and grains, while providing an initial insight into the corresponding fungal population. To facilitate this objective, four water kefirs were sourced from the UK, Canada and the United States. Culture-independent, high-throughput, sequencing-based analyses revealed that the bacterial fraction of each water kefir and grain was dominated by Zymomonas, an ethanol-producing bacterium, which has not previously been detected at such a scale. The other genera detected were representatives of the lactic acid bacteria and acetic acid bacteria. Our analysis of the fungal component established that it was comprised of the genera Dekkera, Hanseniaspora, Saccharomyces, Zygosaccharomyces, Torulaspora and Lachancea. This information will assist in the ultimate identification of the microorganisms responsible for the potentially health-promoting attributes of these beverages.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".