Search for standard-model <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>Z</mml:mi></mml:math> and Higgs bosons decaying into a bottom-antibottom quark pair in proton-antiproton collisions at 1.96 TeV
Bibliographic record
Abstract
The Collider Detector at Fermilab collected a unique sample of jets originating from bottom-quark fragmentation ($b$-jets) by selecting online proton-antiproton ($p\overline{p}$) collisions with a vertex displaced from the $p\overline{p}$ interaction point, consistent with the decay of a bottom-quark hadron. This data set, collected at a center-of-mass energy of 1.96 TeV, and corresponding to an integrated luminosity of $5.4\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$, is used to measure the $Z$-boson production cross section times branching ratio into $b\overline{b}$. The number of $Z\ensuremath{\rightarrow}b\overline{b}$ events is determined by fitting the dijet-mass distribution, while constraining the dominant $b$-jet background, originating from QCD multijet events, with data. The result, $\ensuremath{\sigma}(p\overline{p}\ensuremath{\rightarrow}Z)\ifmmode\times\else\texttimes\fi{}\mathcal{B}(Z\ensuremath{\rightarrow}b\overline{b})=\phantom{\rule{0ex}{0ex}}1.11\ifmmode\pm\else\textpm\fi{}0.08(\mathrm{stat})\ifmmode\pm\else\textpm\fi{}0.14(\mathrm{syst})\text{ }\text{ }\mathrm{nb}$, is the most precise measurement of this process, and is consistent with the standard-model prediction. The data set is also used to search for Higgs-boson production. No significant signal is expected in our data and the first upper limit on the cross section for the inclusive $p\overline{p}\ensuremath{\rightarrow}H\ensuremath{\rightarrow}b\overline{b}$ process at $\sqrt{s}=1.96\text{ }\text{ }\mathrm{TeV}$ is set, corresponding to 33 times the expected standard-model cross section, or $\ensuremath{\sigma}=40.6\text{ }\text{ }\mathrm{pb}$, at the 95% confidence level.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".