Status and Future Evolution of the ATLAS Offline Software
Bibliographic record
Abstract
These proceedings give a summary of the many software upgrade projects undertaken to prepare ATLAS for the challenges of Run-2 of the LHC. Those projects include a significant reduction of the CPU time required for reconstruction of real data with high average pile-up event rates compared to 2012. This is required to meet the challenges of the expected increase in pileup and the higher data taking rate of up to 1 kHz. By far the most ambitious project is the implementation of a completely new analysis model, based on a new ROOT readable reconstruction format, xAOD. The new model also includes a reduction framework based on a train model to centrally produce skimmed data samples and an analysis framework. These proceedings close with a brief overview of future software projects and plans that will lead up to the coming Long Shutdown 2 as the next major ATLAS software upgrade phase.
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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 | 0.018 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.013 |
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".