Combination of searches for $WW$, $WZ$, and $ZZ$ resonances in $pp$ collisions at $\sqrt{s} = 8$ TeV with the ATLAS detector
Bibliographic record
Abstract
The ATLAS experiment at the CERN Large Hadron Collider has performed searches for new, heavy bosons decaying to $WW$, $WZ$ and $ZZ$ final states in multiple decay channels using 20.3 fb$^{-1}$ of $pp$ collision data at $\sqrt{s} = 8$ TeV. In the current study, the results of these searches are combined to provide a more stringent test of models predicting heavy resonances with couplings to vector bosons. Direct searches for a charged diboson resonance decaying to WZ in the $\ellν\ell'\ell'$ ($\ell = μ, e$) , $\ell\ell q \bar{q}$, $\ell νq \bar{q}$ and fully hadronic final states are combined and upper limits on the rate of production times branching ratio to the $WZ$ bosons are compared with predictions of an extended gauge model with a heavy $W'$ boson. In addition, direct searches for a neutral diboson resonance decaying to $WW$ and $ZZ$ in the $\ell \ell q \bar{q}$, $\ell νq \bar{q}$, and fully hadronic final states are combined and upper limits on the rate of production times branching ratio to the $WW$ and $ZZ$ bosons are compared with predictions for a heavy, spin-2 graviton in an extended Randall--Sundrum model where the Standard Model fields are allowed to propagate in the bulk of the extra dimension.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".