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Record W2021113580 · doi:10.1515/hf.2005.076

Decay fungi from playground wood products in service using 28S rDNA sequence analysis

2005· article· en· W2021113580 on OpenAlexaff
Gyu-Hyeok Kim, Young Woon Lim, Yun-Sang Song, Jae‐Jin Kim

Bibliographic record

VenueHolzforschung · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSchizophyllum communePhanerochaeteChrysosporiumTrametes versicolorBasidiomycotaBotanyBiologyAgaricomycetesFungal DiversityLaccase

Abstract

fetched live from OpenAlex

Abstract In order to establish integrated control strategies of wood degradation, a systematic survey of basidiomycete decay fungi colonizing various wood products in service is a prerequisite to increasing the service life of wood products. As a first step, we initiated a thorough survey of basidiomycete decay fungi colonizing playground wood products. For accurate fungal identification, traditional methods were complemented with molecular methods, including a BLAST search for large-subunit 28S rDNA sequences in Genbank and phylogenetic analysis. A total of 132 basidiomycete fungi, including 30 different fungal taxa, were isolated from 35 playgrounds in 15 different areas. Eight species, Bjerkandera adusta, Ceriporia lacerata, Gloeophyllum trabeum, Peniophora sp., Phanerochaete sordida, Schizophyllum commune, Sisto-trema brinkmannii, and Trametes versicolor, were predominantly isolated. A combination of traditional and molecular tools allowed a more detailed identification and 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)0.000
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.045
GPT teacher head0.251
Teacher spread0.206 · 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

Citations31
Published2005
Admission routes1
Has abstractyes

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