Search for electroweak SUSY production in final states with two $\\tau$-leptons in $\\sqrt{s} = 13$ TeV $pp$ collisions with the ATLAS detector
Bibliographic record
Abstract
Three searches for the direct production of staus or charginos and neutralinos in final states with at least two hadronically decaying $\\tau$-leptons are presented. For chargino and neutralino production, decays via intermediate staus or Wh bosons are considered. The analysis uses a dataset of $pp$ collisions corresponding to an integrated luminosity of $139\\,$fb$^{-1}$, recorded with the ATLAS detector at the Large Hadron Collider at a centre-of-mass energy of $13$ TeV. No significant deviation from the expected Standard Model background is observed and SUSY particle mass limits at 95\\% confidence level are obtained in simplified models. For direct production of $\\tilde{\\chi}_1^+\\tilde{\\chi}_1^-$, chargino masses are excluded up to $970\\,$GeV, while $\\tilde{\\chi}_1^{\\pm}$ and $\\tilde{\\chi}_2^0$ masses up to $1160\\,$GeV ($330\\,$GeV) are excluded for $\\tilde{\\chi}_1^{\\pm}\\tilde{\\chi}_2^0$/$\\tilde{\\chi}_1^+\\tilde{\\chi}_1^-$ production decaying via staus ($Wh$ bosons). Stau masses up to $480\\,$GeV are excluded for mass degenerate $\\tilde{\\tau}_{L,R}$ scenarios and up to $410\\,$GeV for $\\tilde{\\tau}_L$-only scenarios. The first sensitivity to $\\tilde{\\tau}_R$-only scenarios is presented here, with $\\tilde{\\tau}_R$ masses excluded up to $330\\,$GeV.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".