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Record W4211167435 · doi:10.1002/yea.3699

Yeasts from temperate forests

2022· article· en· W4211167435 on OpenAlexaff
Simone Mozzachiodi, Feng‐Yan Bai, Petr Baldrián, Graham Bell, Kyria Boundy‐Mills, Pietro Buzzini, Neža Čadež, Francisco A. Cubillos, Sofia Dashko, Roumen Dimitrov, Kaitlin J. Fisher, Brian Gibson, Dilnora Gouliamova, Duncan Greig, Lina Heistinger, Chris Todd Hittinger, Marina Jecmenica, Vassiliki Koufopanou, Christian R. Landry, Tereza Mašínová, Е. С. Наумова, Dana A. Opulente, Jacqueline Peña, Uroš Petrovič, Isheng Jason Tsai, Benedetta Turchetti, Pablo Villarreal, Andrey Yurkov, Gianni Liti, Primrose J. Boynton

Bibliographic record

VenueYeast · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsUniversité LavalPROTEOMcGill University
FundersOffice of the Vice Chancellor for Research and InnovationWisconsin Alumni Research FoundationDivision of Graduate EducationGoddard Space Flight CenterNational Institute of Food and AgricultureGreat Lakes Bioenergy Research CenterBulgarian National Science FundGrantová Agentura České RepublikyUniversity of Wisconsin-MadisonU.S. Department of AgricultureU.S. Department of EnergyNational Science Foundation
KeywordsBiologyTemperate climateTemperate rainforestTemperate forestEcologyEcosystem

Abstract

fetched live from OpenAlex

Yeasts are ubiquitous in temperate forests. While this broad habitat is well-defined, the yeasts inhabiting it and their life cycles, niches, and contributions to ecosystem functioning are less understood. Yeasts are present on nearly all sampled substrates in temperate forests worldwide. They associate with soils, macroorganisms, and other habitats and no doubt contribute to broader ecosystem-wide processes. Researchers have gathered information leading to hypotheses about yeasts' niches and their life cycles based on physiological observations in the laboratory as well as genomic analyses, but the challenge remains to test these hypotheses in the forests themselves. Here, we summarize the habitat and global patterns of yeast diversity, give some information on a handful of well-studied temperate forest yeast genera, discuss the various strategies to isolate forest yeasts, and explain temperate forest yeasts' contributions to biotechnology. We close with a summary of the many future directions and outstanding questions facing researchers in temperate forest yeast ecology. Yeasts present an exciting opportunity to better understand the hidden world of microbial ecology in this threatened and global habitat.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.216
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations51
Published2022
Admission routes1
Has abstractyes

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