The ATLAS TAGS database distribution and management – Operational challenges of a multi-terabyte distributed database
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.
Bibliographic record
Abstract
The TAG files store summary event quantities that allow a quick selection of interesting events. This data will be produced at a nominal rate of 200 Hz, and is uploaded into a relational database for access from websites and other tools. The estimated database volume is 6TB per year, making it the largest application running on the ATLAS relational databases, at CERN and at other voluntary sites. The sheer volume and high rate of production makes this application a challenge to data and resource management, in many aspects. This paper will focus on the operational challenges of this system. These include: uploading the data from files to the CERN's and remote sites' databases; distributing the TAG metadata that is essential to guide the user through event selection; controlling resource usage of the database, from the user query load to the strategy of cleaning and archiving of old TAG data. © 2010 IOP Publishing Ltd.
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 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 | 0.001 | 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 | 0.001 |
| 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 it