Measurement of the production cross-section of a single top quark in association with a W boson at 8 TeV with the ATLAS experiment
Bibliographic record
Abstract
The cross-section for the production of a single top quark in association with a W boson in proton-proton collisions at √s=8TeV is measured. The dataset corresponds to an integrated luminosity of 20.3 fb−1, collected by the ATLAS detector in 2012 at the Large Hadron Collider at CERN. Events containing two leptons and one central b-jet are selected. The W t signal is separated from the backgrounds using boosted decision trees, each of which combines a number of discriminating variables into one classifier. Production of W t events is observed with a significance of 7.7σ. The cross-section is extracted in a profile likelihood fit to the classifier output distributions. The W t cross-section, inclusive of decay modes, is measured to be 23.0 ± 1.3(stat.) − 3.5 + 3.2 (syst.)±1.1(lumi.) pb. The measured cross-section is used to extract a value for the CKM matrix element |V tb | of 1.01 ± 0.10 and a lower limit of 0.80 at the 95% confidence level. The cross-section for the production of a top quark and a W boson is also measured in a fiducial acceptance requiring two leptons with p T > 25 GeV and |η| < 2.5, one jet with p T > 20 GeV and |η| < 2.5, and E T miss > 20 GeV, including both W t and top-quark pair events as signal. The measured value of the fiducial cross-section is 0.85 ± 0.01(stat.) − 0.07 + 0.07 (syst.)±0.03(lumi.) pb.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".