USAGE: a web-based approach towards the analysis of SAGE data
Bibliographic record
Abstract
MOTIVATION: SAGE enables the determination of genome-wide mRNA expression profiles. A comprehensive analysis of SAGE data requires software, which integrates (statistical) data analysis methods with a database system. Furthermore, to facilitate data sharing between users, the application should reside on a central server and be accessed via the internet. Since such an application was not available we developed the USAGE package. RESULTS: USAGE is a web-based application that comprises an integrated set of tools, which offers many functions for analysing and comparing SAGE data. Additionally, USAGE includes a statistical method for the planning of new SAGE experiments. USAGE is available in a multi-user environment giving users the option of sharing data. USAGE is interfaced to a relational database to store data and analysis results. The USAGE query editor allows the composition of queries for searching this database. Several database functions have been included which enable the selection and combination of data. USAGE provides the biologist increased functionality and flexibility for analysing SAGE data. AVAILABILITY: USAGE is freely accessible for academic institutions at http://www.cmbi.kun.nl/usage/. The source code of USAGE is freely available for academic institutions on request from the first author.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".