Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".