Search for massive supersymmetric particles decaying to many jets using the ATLAS detector inppcollisions ats=8 TeV
Bibliographic record
Abstract
Results of a search for decays of massive particles to fully hadronic final states are presented. This search uses $20.3\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$ of data collected by the ATLAS detector in $\sqrt{s}=8\text{ }\text{ }\mathrm{TeV}$ proton-proton collisions at the LHC. Signatures based on high jet multiplicities without requirements on the missing transverse momentum are used to search for $R$-parity-violating supersymmetric gluino pair production with subsequent decays to quarks. The analysis is performed using a requirement on the number of jets, in combination with separate requirements on the number of $b$-tagged jets, as well as a topological observable formed from the scalar sum of the mass values of large-radius jets in the event. Results are interpreted in the context of all possible branching ratios of direct gluino decays to various quark flavors. No significant deviation is observed from the expected Standard Model backgrounds estimated using jet counting as well as data-driven templates of the total-jet-mass spectra. Gluino pair decays to ten or more quarks via intermediate neutralinos are excluded for a gluino with mass ${m}_{\stackrel{\texttildelow{}}{g}}<1\text{ }\text{ }\mathrm{TeV}$ for a neutralino mass ${m}_{{\stackrel{\texttildelow{}}{\ensuremath{\chi}}}_{1}^{0}}=500\text{ }\text{ }\mathrm{GeV}$. Direct gluino decays to six quarks are excluded for ${m}_{\stackrel{\texttildelow{}}{g}}<917\text{ }\text{ }\mathrm{GeV}$ for light-flavor final states, and results for various flavor hypotheses are presented.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.003 | 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".