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Record W4406638770 · doi:10.1139/cjb-2024-0130

First record of trichomycete fungi from Rouge National Urban Park and Greater Toronto Area

2025· article· en· W4406638770 on OpenAlexafffundvenueabout
Maija Lehn, Yan Wang

Bibliographic record

VenueBotany · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNational parkBiologyROUGEBotanyArchaeologyEcologyGeography

Abstract

fetched live from OpenAlex

Insect gut-dwelling fungi, also known as trichomycete fungi, are obligate symbionts that reside in the digestive tracts of freshwater insect larvae or nymphs. Trichomycete fungi have been extensively documented worldwide and hold significant ecological and evolutionary importance. However, their distribution in Rouge National Urban Park (RNUP) and Greater Toronto Area (GTA), Ontario, Canada, remains underexplored. To enhance our understanding of microbial fungal resources in Canada and to examine trichomycetes diversity in urban environments, a comprehensive study was conducted in RNUP and associated watersheds in GTA, including Highland Creek, Little Rouge Creek, and West Duffins Creek. A total of 28 collection sites were sampled, leading to the identification of various species new to the area, including Caudomyces sp., Ejectosporus trisporus, Genistelloides sp., Stachylina paucispora, Stachylina penetralis, Trichozygospora chironomidarum, Smittium caudatum, Smittium culicis, and Smittium simulii. Our findings significantly expand the known distribution of these symbiotic fungi in urban environments and underscore the importance of these habitats as reservoirs of microbial fungal 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 score0.120
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.219
Teacher spread0.209 · 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

Citations2
Published2025
Admission routes4
Has abstractyes

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