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Record W2406422335 · doi:10.1007/978-1-62703-438-8_11

Yeast as a Platform to Explore Polyglutamine Toxicity and Aggregation

2013· review· en· W2406422335 on OpenAlexaff
Martin L. Duennwald

Bibliographic record

VenueMethods in molecular biology · 2013
Typereview
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsWestern University
Fundersnot available
KeywordsYeastSaccharomyces cerevisiaeProtein aggregationModel organismBiologyToxicityOrganismComputational biologyCell biologyGeneticsChemistryGene

Abstract

fetched live from OpenAlex

Protein misfolding is associated with many neurodegenerative diseases, including neurodegenerative diseases caused by polyglutamine expansion proteins, such as Huntington's disease. The model organism baker's yeast (Saccharomyces cerevisiae) has provided important general insights into the basic cellular mechanisms underlying protein misfolding. Furthermore, experiments in yeast have identified cellular factors that modulate the toxicity and the aggregation associated with polyglutamine expansion proteins. Notably, many features discovered in yeast have been proven to be highly relevant in other model organisms and in human pathology. The experimental protocols depicted here serve to reliably determine polyglutamine toxicity and polyglutamine aggregation in yeast.

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: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.004

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 head0.168
GPT teacher head0.465
Teacher spread0.296 · 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
GenreReview

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

Citations19
Published2013
Admission routes1
Has abstractyes

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