Search for single vector-like $B$ quark production and decay via $B\rightarrow bH(b\bar{b})$ in $pp$ collisions at $\sqrt{s} = 13$ TeV with the ATLAS detector
Bibliographic record
Abstract
A bstract A search is presented for single production of a vector-like B quark decaying into a Standard Model b -quark and a Standard Model Higgs boson, which decays into a $$ b\overline{b} $$ b b ¯ pair. The search is carried out in 139 fb − 1 of $$ \sqrt{s} $$ s = 13 TeV proton-proton collision data collected by the ATLAS detector at the LHC between 2015 and 2018. No significant deviation from the Standard Model background prediction is observed, and mass-dependent exclusion limits at the 95% confidence level are set on the resonance production cross-section in several theoretical scenarios determined by the couplings c W , c Z and c H between the B quark and the Standard Model W , Z and Higgs bosons, respectively. For a vector-like B occurring as an isospin singlet, the search excludes values of c W greater than 0.45 for a B resonance mass ( m B ) between 1.0 and 1.2 TeV. For 1 . 2 TeV < m B < 2 . 0 TeV, c W values larger than 0.50–0.65 are excluded. If the B occurs as part of a ( B, Y ) doublet, the smallest excluded c Z coupling values range between 0.3 and 0.5 across the investigated resonance mass range 1 . 0 TeV < m B < 2 . 0 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".