Measurements of Higgs boson production via gluon-gluon fusion and vector-boson fusion using $H\rightarrow WW^\ast \rightarrow \ellν\ellν$ decays in $pp$ collisions with the ATLAS detector and their effective field theory interpretations
Bibliographic record
Abstract
Higgs boson production cross-sections via gluon-gluon fusion and vector-boson fusion in proton-proton collisions are measured in the $H\rightarrow WW^\ast \rightarrow \ellν\ellν$ decay channel. The Large Hadron Collider delivered proton-proton collisions at a centre-of-mass energy of $13\,\textrm{TeV}$ between 2015 and 2018, which were recorded by the ATLAS detector, corresponding to an integrated luminosity of $140\,\textrm{fb}^{-1}$. The total cross-sections for Higgs boson production by gluon-gluon fusion and vector-boson fusion times the $H\rightarrow WW^\ast$ branching ratio are measured to be $12.4^{+1.3}_{-1.2}\,\textrm{pb}$ and $0.79^{+0.18}_{-0.16}\,\textrm{pb}$, respectively, in agreement with the Standard Model predictions. Higgs boson production is further characterised through measurements of Simplified Template Cross-Sections in a total of fifteen kinematic fiducial regions. A new scheme of kinematic fiducial regions has been introduced to enhance the sensitivity to CP-violating effects in Higgs boson interactions. Both schemes are used to constrain CP-even and CP-odd dimension-six operators in the Standard Model 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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".