Measurement of the charge asymmetry in top quark pair production in pp collisions at √<i>s</i>= 7 TeV using the ATLAS detector
Bibliographic record
Abstract
We present a measurement of the charge asymmetry in top-antitop production using data corresponding to an integrated luminosity of 0.70 fb-1 of proton-proton collisions at √s = 7 TeV collected by the ATLAS detector. The top pair events decaying semileptonically (lepton+jets channel) to either an electron or muon, missing transverse energy and at least four jets are selected. The reconstruction of the events was performed using a kinematic likelihood approach. The difference of absolute values of top and antitop rapidities is used to define the charge asymmetry: AC = (N(|ΔY| > 0) − N(|ΔY| < 0)) / (N(|ΔY| > 0) + N(|ΔY| < 0)). To allow comparisons with theory calculations, a Bayesian unfolding technique is applied to correct the measured |ΔY| distributions for acceptance and detector effects. The top charge asymmetry in both channels (e and mu) after correction is measured to be: AC = -0.009 ± 0.023(stat) ± 0.032(syst) (e+jets channel) and AC = -0.028 ± 0.019(stat) ± 0.022(syst) (μ+jets channel) giving a combined result of : AC = -0.024 ± 0:016(stat) ± 0.023(syst). These results are compatible with the Standard Model predictions of AC = 0.006.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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".