Bibliographic record
Abstract
The ATLAS experiment is a general purpose detector designed to exploit the full potential of the Large Hadron Collider at both low and high luminosity running. Central to the ATLAS physics program is what one can term discovery physics. In defining the calorimeter design goals this discovery physics has been a major consideration. An important design touchstone was the ability to discover a standard model Higgs over a wide mass range. This is shown in Fig.1. At low masses the energy resolution for photons, and fine electromagnetic spatial resolution, are at a premium in order to distinguish photons from 0 π and to reconstruct the channel H γγ → against a large background; this sets the design goals for the electromagnetic calorimeter system. In the intermediate mass region the decay channel H l l l l + − + − → again mandates high quality electromagnetic calorimetry over a wide rapidity range. In the high mass region up to 1 TeV, the ability to identify jets and to reconstruct jet invariant masses is a major design consideration. Many “discovery” topics, such as supersymmetery, depend on the detection of missing energy and require hermetic hadronic calorimetry. These are only the major design goals, and clearly more optimization than can be covered here has gone on in the design of ATLAS, see [1]. A summary of the calorimeter design goals, and the chosen technologies is given in Fig. 2. At this meeting the construction and testing of the electromagnetic calorimeters was covered in separate contributions, see [2], [3]. Here we restrict ourselves to a discussion of the Forward Calorimeter, the assembly of the end cap calorimeters, and plans for combined test beams.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.051 | 0.019 |
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".