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Record W3185787644 · doi:10.1128/aem.00329-21

Retracted and Republished from: “Substrate-Specific Differential Gene Expression and RNA Editing in the Brown Rot Fungus <i>Fomitopsis pinicola</i> ”

2021· article· en· W3185787644 on OpenAlexaff
Baojun Wu, Jill Gaskell, Benjamin W. Held, Cristina Toapanta, Thu V. Vuong, Steven Ahrendt, Anna Lipzen, Jiwei Zhang, Jonathan S. Schilling, Emma R. Master, Igor V. Grigoriev, Robert A. Blanchette, Dan Cullen, David S. Hibbett

Bibliographic record

VenueApplied and Environmental Microbiology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEnzyme-mediated dye degradation
Canadian institutionsUniversity of Toronto
FundersNational Science Foundation
KeywordsBotanyFungusBiologySubstrate (aquarium)Ecology

Abstract

fetched live from OpenAlex

is able to modify gene expression (transcription levels) across different substrate species and culture conditions. Many of the genes involved encode enzymes with known or predicted functions in wood decay. This study provides clues to how wood-decaying fungi may adjust their arsenal of decay enzymes to accommodate different host substrates.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.747

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.2230.124

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 head0.008
GPT teacher head0.160
Teacher spread0.152 · 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.

Study designNot applicable
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

Citations4
Published2021
Admission routes1
Has abstractyes

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