Simultaneous measurements of the t t ¯, W+W-, and Z/γ∗ →ττ production cross-sections in pp collisions at s =7TeV with the ATLAS detector SIMULTANEOUS MEASUREMENTS OF THE t t ¯, ... G. AAD et al.
Bibliographic record
Abstract
© 2015 CERN, for the ATLAS Collaboration. Simultaneous measurements of the tt¯, W+W-, and Z/γ∗→ττ production cross-sections using an integrated luminosity of 4.6fb-1 of pp collisions at s=7TeV collected by the ATLAS detector at the LHC are presented. Events are selected with two high transverse momentum leptons consisting of an oppositely charged electron and muon pair. The three processes are separated using the distributions of the missing transverse momentum of events with zero and greater than zero jet multiplicities. Measurements of the fiducial cross-section are presented along with results that quantify for the first time the underlying correlations in the predicted and measured cross-sections due to proton parton distribution functions. These results indicate that the correlated next-to-leading-order predictions for tt¯ and Z/γ∗→ττ underestimate the data, while those at next-to-next-to-leading-order generally describe the data well. The full cross-sections are measured to be σ(tt¯)=181.2±2.8-9.5+9.7±3.3±3.3pb, σ(W+W-)=53.3±2.7-8.0+7.3±1.0±0.5pb, and σ(Z/γ∗→ττ)=1174±24-87+72±21±9pb, where the cited uncertainties are due to statistics, systematic effects, luminosity and the LHC beam energy measurement, respectively. The W+W- measurement includes the small contribution from Higgs boson decays, H→W+W-.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".