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Record W4280513943 · doi:10.1093/femsyr/foac028

Molecular approaches improving our understanding of<i>Brettanomyces</i>physiology

2022· review· en· W4280513943 on OpenAlexfundno aff
Cristián Varela, Anthony R. Borneman

Bibliographic record

VenueFEMS Yeast Research · 2022
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsnot available
FundersWine AustraliaAustralian GovernmentAlberta Water Research Institute
KeywordsWinemakingBiologyBrewingFood spoilageFood scienceBiotechnologyFermentationBacteriaGenetics

Abstract

fetched live from OpenAlex

Brettanomyces species, and particularly B. bruxellensis as the most studied representative, are strongly linked to industrial fermentation processes. This association is considered either positive or undesirable depending on the industry. While in some brewing applications and in kombucha production Brettanomyces yeasts contribute to the flavour and aroma profile of these beverages, in winemaking and bioethanol production Brettanomyces is considered a spoilage or contaminant microorganism. Nevertheless, understanding Brettanomyces biology and metabolism in detail will benefit all industries. This review discusses recent molecular biology tools including genomics, transcriptomics, and genetic engineering techniques that can improve our understanding of Brettanomyces physiology and how these approaches can be used to make the industrial potential of this species a reality.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.452
GPT teacher head0.388
Teacher spread0.064 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations5
Published2022
Admission routes1
Has abstractyes

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