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Record W2109317704 · doi:10.1139/w10-001

Comparison of effectiveness of wood decay fungi maintained by annual subculture on agar and stored in sterile water for 18 years

2010· article· en· W2109317704 on OpenAlexvenueno aff
Dana L. Richter, Laura Kangas, Jill K. Smith, Peter E. Laks

Bibliographic record

VenueCanadian Journal of Microbiology · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsnot available
FundersMichigan Technological University
KeywordsSubculture (biology)AgarMyceliumFungusTrametes versicolorSterile waterBiologyStrain (injury)BotanyPotato dextrose agarHorticultureCold storageAgar plateBacteria

Abstract

fetched live from OpenAlex

Fourteen isolates of basidiomycete decay fungi (12 species) were maintained for 18 years on agar slants transferred annually and also stored as mycelium-agar cores under cold sterile water without subculture. Isolates stored by each method were evaluated for decay effectiveness using a standard laboratory accelerated soil-block decay test. Effectiveness was measured by mean percent mass loss of wood blocks. There was no significant difference (p < or = 0.05) in decay effectiveness between storage methods for 12 of the fungus isolates tested. For the 2 fungi that showed a significant difference in the amount of decay with respect to storage method, 1 fungus (Fomitopsis lilacinogilva) produced more decay by the strain maintained as an agar slant, while the other fungus (Trametes versicolor) produced more decay by the strain stored in sterile water. Results suggested that storage under sterile water is an easy and effective method to store isolates of decay fungi for long periods, but as with any microbial storage method, careful monitoring of isolates upon revival is necessary.

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: Bench or experimental · Consensus signal: Bench or experimental
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)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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 designBench or experimental
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

Citations13
Published2010
Admission routes1
Has abstractyes

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