Updated search for the standard model Higgs boson in events with jets and missing transverse energy using the full CDF data set
Bibliographic record
Abstract
We present an updated search for the Higgs boson produced in association with a vector boson in the final state with missing transverse energy and two jets. We use the full CDF data set corresponding to an integrated luminosity of $9.45\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$ at a proton-antiproton center-of-mass energy of $\sqrt{s}=1.96\text{ }\text{ }\mathrm{TeV}$. New to this analysis is the inclusion of a $b$-jet identification algorithm specifically optimized for $H\ensuremath{\rightarrow}b\overline{b}$ searches. Across the Higgs boson mass range $90\ensuremath{\le}{m}_{H}\ensuremath{\le}150\text{ }\text{ }\mathrm{GeV}/{c}^{2}$, the expected 95% credibility level upper limits on the $VH$ production cross section times the $H\ensuremath{\rightarrow}b\overline{b}$ branching fraction are improved by an average of 14% relative to the previous analysis. At a Higgs boson mass of $125\text{ }\text{ }\mathrm{GeV}/{c}^{2}$, the observed (expected) limit is 3.06 (3.33) times the standard model prediction, corresponding to one of the most sensitive searches to date in this final state.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".