Measurements of jet vetoes and azimuthal decorrelations in dijet events produced in $$pp$$ p p collisions at $$\sqrt{s}=7\,\mathrm{TeV}$$ s = 7 TeV using the ATLAS detector
Bibliographic record
Abstract
Additional jet activity in dijet events is measured using [Formula: see text] collisions at ATLAS at a centre-of-mass energy of [Formula: see text], for jets reconstructed using the [Formula: see text] algorithm with radius parameter [Formula: see text]. This is done using variables such as the fraction of dijet events without an additional jet in the rapidity interval bounded by the dijet subsystem and correlations between the azimuthal angles of the dijet s. They are presented, both with and without a veto on additional jet activity in the rapidity interval, as a function of the scalar average of the transverse momenta of the dijet s and of the rapidity interval size. The double differential dijet cross section is also measured as a function of the interval size and the azimuthal angle between the dijet s. These variables probe differences in the approach to resummation of large logarithms when performing QCD calculations. The data are compared to powheg, interfaced to the pythia 8 and herwig parton shower generators, as well as to hej with and without interfacing it to the ariadne parton shower generator. None of the theoretical predictions agree with the data across the full phase-space considered; however, powheg+pythia 8 and hej+ariadne are found to provide the best agreement with the data. These measurements use the full data sample collected with the ATLAS detector in [Formula: see text][Formula: see text] collisions at the LHC and correspond to integrated luminosities of [Formula: see text] and [Formula: see text] for data collected during 2010 and 2011, respectively.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".