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Record W3198332574 · doi:10.1016/j.isci.2021.103098

Global patterns in culturable soil yeast diversity

2021· article· en· W3198332574 on OpenAlexafffund
Himeshi Samarasinghe, Yi Lü, Renad Aljohani, Ahmad Al-Amad, Heather Yoell, Jianping Xu

Bibliographic record

VenueiScience · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYeasts and Rust Fungi Studies
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaMcMaster University
KeywordsMetagenomicsEcosystemYeastSoil microbiologyBiologyEcologyDecomposerBiodiversityFungal DiversityMicrobial ecologyMicroorganismSoil waterBacteria

Abstract

fetched live from OpenAlex

Yeasts, broadly defined as unicellular fungi, fulfill essential roles in soil ecosystems as decomposers and nutrition sources for fellow soil-dwellers. Broad-scale investigations of soil yeasts pose a methodological challenge as metagenomics are of limited use for identifying this group of fungi. Here we characterize global soil yeast diversity using fungal DNA barcoding on 1473 yeasts cultured from 3826 soil samples obtained from nine countries in six continents. We identify mean annual precipitation and international air travel as two significant correlates with soil yeast community structure and composition worldwide. Evidence for anthropogenic influences on soil yeast communities, directly via travel and indirectly via altered rainfall patterns resulting from climate change, is concerning as we found common infectious yeasts frequently distributed in soil in several countries. Our discovery of 41 putative novel species highlights the continued need for culture-based studies to advance our knowledge of environmental yeast diversity.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.011
GPT teacher head0.237
Teacher spread0.226 · 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

Citations20
Published2021
Admission routes2
Has abstractyes

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