Study of the (Formula presented.) and (Formula presented.) decays with the ATLAS detector
Bibliographic record
Abstract
© 2015, CERN for the benefit of the ATLAS collaboration. The decays (Formula presented.) and (Formula presented.) are studied with the ATLAS detector at the LHC using a dataset corresponding to integrated luminosities of 4.9 and 20.6 fb -1 of pp collisions collected at centre-of-mass energies (Formula presented.) TeV and 8 TeV, respectively. Signal candidates are identified through (Formula presented.) and (Formula presented.) decays. With a two-dimensional likelihood fit involving the (Formula presented.) reconstructed invariant mass and an angle between the (Formula presented.) candidate momenta in the muon pair rest frame, the yields of (Formula presented.) and (Formula presented.), and the transverse polarisation fraction in (Formula presented.) decay are measured. The transverse polarisation fraction is determined to be (Formula presented.) = 0.38 \\pm 0.23 \\pm 0.07(Formula presented.), and the derived ratio of the branching fractions of the two modes is (Formula presented.), where the first error is statistical and the second is systematic. Finally, a sample of (Formula presented.) decays is used to derive the ratios of branching fractions (Formula presented.) and (Formula presented.) = 10.4 \\pm 3.1 \\pm 1.5 \\pm 0.6(Formula presented.), where the third error corresponds to the uncertainty of the branching fraction of (Formula presented.) decay. The available theoretical predictions are generally consistent with the measurement.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".