Search for charginos and neutralinos in final states with two boosted hadronically decaying bosons and missing transverse momentum in $pp$ collisions at $\sqrt {s}$ = 13 TeV with the ATLAS detector
Bibliographic record
Abstract
A search for charginos and neutralinos at the Large Hadron Collider is reported using fully hadronic final states and missing transverse momentum. Pair-produced charginos or neutralinos are explored, each decaying into a high-$p_{\text{T}}$ Standard Model weak boson. Fully-hadronic final states are studied to exploit the advantage of the large branching ratio, and the efficient background rejection by identifying the high-$p_{\text{T}}$ bosons using large-radius jets and jet substructure information. An integrated luminosity of 139 fb$^{-1}$ of proton-proton collision data collected by the ATLAS detector at a center-of-mass energy of 13 TeV is used. No significant excess is found beyond the Standard Model expectation. The 95% confidence level exclusion limits are set on wino or higgsino production with varying assumptions in the decay branching ratios and the type of the lightest supersymmetric particle. A wino (higgsino) mass up to 1060 (900) GeV is excluded when the lightest SUSY particle mass is below 400 (240) GeV and the mass splitting is larger than 400 (450) GeV. The sensitivity to high-mass wino and higgsino is significantly extended compared with the previous LHC searches using the other final states.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".