Search for heavy resonances in final states with four leptons and missing transverse momentum or jets in $pp$ collisions at $\sqrt{s} = 13$ TeV with the ATLAS detector
Bibliographic record
Abstract
A search for a new heavy boson produced via gluon-fusion in the four-lepton channel with missing transverse momentum or jets is performed. The search uses proton-proton collision data equivalent to an integrated luminosity of 139 fb$^{-1}$ at a centre-of-mass energy of 13 TeV collected by the ATLAS detector between 2015 and 2018 at the Large Hadron Collider. This study explores the decays of heavy bosons: $R\rightarrow SH$ and $A\rightarrow ZH$, where $R$ is a CP-even boson, $A$ is a CP-odd boson, $H$ is a CP-even boson, and $S$ is considered to decay into invisible particles that are candidates for dark matter. In these processes, $S\rightarrow \textrm{invisible}$ and $H\rightarrow ZZ$. The $Z$ boson associated with the heavy scalar boson $H$ decays into all decay channels of the $Z$ boson. The mass range under consideration is 390-1300 (320-1300) GeV for the $R$ ($A$) boson and 220-1000 GeV for the $H$ boson. No significant deviation from the Standard Model backgrounds is observed. The results are interpreted as upper limits at a 95% confidence level on the cross-section times the branching ratio of the heavy resonances.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".