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Record W2075180808 · doi:10.2174/187152606778249890

Serial Analysis of Gene Expression in Eukaryotic Pathogens

2006· review· en· W2075180808 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInfectious Disorders - Drug Targets · 2006
Typereview
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsExpression (computer science)GeneGene expressionBiologyGeneticsComputational biologyEvolutionary biologyComputer science

Abstract

fetched live from OpenAlex

The tag-based method of serial analysis of gene expression (SAGE) has been used to measure mRNA abundance and differential expression in a variety of organisms including several parasites and fungal pathogens. SAGE is based on the collection of short sequence tags as a measure of transcript abundance and the method provides an alternative, and in some instances, complementary approach to array-based methods of measuring differential gene expression. These methods are being used to improve our molecular understanding of the pathogenesis of eukaryotic microbes and SAGE in particular presents valuable opportunities for gene discovery and genome annotation. For eukaryotic pathogens, the SAGE method has been employed for the parasites Plasmodium falciparum, Toxoplasma gondii and Giardia lamblia, as well as fungal pathogens of plants (Magnaporthe grisea, Blumeria graminis, Ustilago maydis) and humans (Cryptococcus neoformans, Coccidiodes posadasii, Trichophyton rubrum). The accumulating information promises to speed the identification of key pathogen functions for virulence and proliferation in the host with the hope that some of these will represent important targets for drug and vaccine development.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.960
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.014
GPT teacher head0.293
Teacher spread0.279 · 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