Search for single production of vector-like quarks decaying into Wb in pp collisions at $$\sqrt{s} = 8$$ s = 8 TeV with the ATLAS detector
Bibliographic record
Abstract
A search for singly produced vector-like $Q$ quarks, where $Q$ can be either a $T$ quark with charge $+2/3$ or a $Y$ quark with charge $-4/3$, is performed in proton-proton collisions recorded with the ATLAS detector at the LHC. The dataset corresponds to an integrated luminosity of 20.3 fb$^{-1}$ and was produced with a centre-of-mass energy of $\sqrt{s}=8$ TeV. This analysis targets $Q \to Wb$ decays where the $W$ boson decays leptonically. A veto on massive large-radius jets is used to reject the dominant $t\bar{t}$ background. The reconstructed $Q$-candidate mass, ranging from 0.4 to 1.2 TeV, is used in the search to discriminate signal from background processes. No significant deviation from the Standard Model expectation is observed, and limits are set on the $Q \to Wb$ cross-section times branching ratio. The results are also interpreted as limits on the $QWb$ coupling and the mixing with the Standard Model sector for a singlet $T$ quark or a $Y$ quark from a doublet. $T$ quarks with masses below 0.95 TeV are excluded at 95% confidence level, assuming a unit coupling and a BR$(T\rightarrow Wb) = 0.5$, whereas the expected limit is 1.10 TeV.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".