Search for Higgs bosons produced in association with<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>b</mml:mi></mml:math>quarks
Bibliographic record
Abstract
We present a search for neutral Higgs bosons $\ensuremath{\phi}$ decaying into $b\overline{b}$, produced in association with $b$ quarks in $p\overline{p}$ collisions. This process could be observable in supersymmetric models with high values of $\mathrm{tan}\ensuremath{\beta}$. The event sample corresponds to $2.6\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$ of integrated luminosity collected with the CDF II detector at the Fermilab Tevatron collider. We search for an enhancement in the mass of the two leading jets in events with three jets identified as coming from $b$ quarks using a displaced vertex algorithm. A data-driven procedure is used to estimate the dijet mass spectrum of the nonresonant multijet background. The contributions of backgrounds and a possible Higgs boson signal are determined by a two-dimensional fit of the data, using the dijet mass together with an additional variable which is sensitive to the flavor composition of the three tagged jets. We set mass-dependent limits on $\ensuremath{\sigma}(p\overline{p}\ensuremath{\rightarrow}\ensuremath{\phi}b)\ifmmode\times\else\texttimes\fi{}\mathcal{B}(\ensuremath{\phi}\ensuremath{\rightarrow}b\overline{b})$ which are applicable for a narrow scalar particle $\ensuremath{\phi}$ produced in association with $b$ quarks. We also set limits on $\mathrm{tan}\ensuremath{\beta}$ in supersymmetric Higgs models including the effects of the Higgs boson width.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".