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Record W6931783823 · doi:10.5683/sp3/8ixktf

Systemic infection of Bryoria (Lecanoromycetes, Ascomycota) by Athelia (Agaricomycetes, Basidiomycota) in western North America

2023· dataset· en· W6931783823 on OpenAlexaffabout

Bibliographic record

VenueOpen MIND · 2023
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicOcular Disorders and Treatments
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsLichenThallusGenusTaxonomy (biology)Basidium

Abstract

fetched live from OpenAlex

Abstract Bryoria (Parmeliaceae, Ascomycota) is one of the dominant genera of hair lichens in western North America and is characteristic of high-elevation conifer forest ecosystems. In areas where Bryoria is abundant, it is common to find thalli in which the thalline filaments become conglutinated, forming brittle dead zones. After sampling Bryoria thalli across western Canada and the northwestern United States at different times of the year, we found this dieback phenomenon is associated with the winter growth of a mold-forming basidiomycete. We report that this fungus belongs to Athelia (Atheliaceae, Basidiomycota) a genus known to contain lichen pathogens, most notably A. arachnoidea. By sequencing a combination of genetic markers – nuc rDNA ITS1-5.8S-ITS2 (ITS), partial nuc 28S rDNA (28S), and partial translation elongation factor 1-α (TEF1) – paired with morphometric analyses, we reveal the involvement of at least three additional lineages of lichen-associated Athelia and describe one as a new species, Athelia abscondita. A. abscondita is morphologically distinguished from other Athelia species by its basidia and basidiospores, was found to frequently infect members of Bryoria sect. Implexae, and was occasionally on other foliose and fruticose species within Parmeliaceae.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.096
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

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

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 head0.013
GPT teacher head0.275
Teacher spread0.262 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations1
Published2023
Admission routes2
Has abstractyes

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Same venueOpen MINDSame topicOcular Disorders and TreatmentsFrench-language works237,207