Searches for heavy long-lived sleptons and R-hadrons with the ATLAS detector in pp collisions at √s=7 TeV
Bibliographic record
Abstract
A search for long-lived particles is performed using a data sample of 4.7 fb−1 from proton–proton collisions at a centre-of-mass energy √s =7 TeV collected by the ATLAS detector at the LHC. No excess is observed above the estimated background and lower limits, at 95% confidence level, are set on the mass of the long-lived particles in different scenarios, based on their possible interactions in the inner detector, the calorimeters and the muon spectrometer. Long-lived staus in gauge-mediated SUSY-breaking models are excluded up to a mass of 300 GeV for tanβ =5–20. Directly produced long-lived sleptons are excluded up to a mass of 278 GeV. R-hadrons, composites of gluino (stop, sbottom) and light quarks, are excluded up to a mass of 985 GeV (683 GeV, 612 GeV) when using a generic interaction model. Additionally two sets of limits on R-hadrons are obtained that are less sensitive to the interaction model for R-hadrons. One set of limits is obtained using only the inner detector and calorimeter observables, and a second set of limits is obtained based on the inner detector alone.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".