Integrated and differential fiducial cross-section measurements for the vector boson fusion production of the Higgs boson in the H→WW*→eνμν decay …
Bibliographic record
Abstract
The vector-boson production cross section for the Higgs boson decay in the $H\ensuremath{\rightarrow}W{W}^{*}\ensuremath{\rightarrow}e\ensuremath{\nu}\ensuremath{\mu}\ensuremath{\nu}$ channel is measured as a function of kinematic observables sensitive to the Higgs boson production and decay properties as well as integrated in a fiducial phase space. The analysis is performed using the proton-proton collision data collected by the ATLAS detector in Run 2 of the LHC at $\sqrt{s}=13\text{ }\text{ }\mathrm{TeV}$ center-of-mass energy, corresponding to an integrated luminosity of $139\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$. The different flavor final state is studied by selecting an electron and a muon originating from a pair of $W$ bosons and compatible with the Higgs boson decay. The data are corrected for the effects of detector inefficiency and resolution, and the measurements are compared with different state-of-the-art theoretical predictions. The differential cross sections are used to constrain anomalous interactions described by dimension-six operators in an effective field theory.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".