Study of the $$B_c^+ \rightarrow J/\psi D_s^+$$ B c + → J / ψ D s + and $$B_c^+ \rightarrow J/\psi D_s^{*+}$$ B c + → J / ψ D s ∗ + decays with the ATLAS detector
Bibliographic record
Abstract
The decays [Formula: see text] and [Formula: see text] are studied with the ATLAS detector at the LHC using a dataset corresponding to integrated luminosities of 4.9 and 20.6 fb[Formula: see text] of pp collisions collected at centre-of-mass energies [Formula: see text] TeV and 8 TeV, respectively. Signal candidates are identified through [Formula: see text] and [Formula: see text] decays. With a two-dimensional likelihood fit involving the [Formula: see text] reconstructed invariant mass and an angle between the [Formula: see text] and [Formula: see text] candidate momenta in the muon pair rest frame, the yields of [Formula: see text] and [Formula: see text], and the transverse polarisation fraction in [Formula: see text] decay are measured. The transverse polarisation fraction is determined to be [Formula: see text], and the derived ratio of the branching fractions of the two modes is [Formula: see text], where the first error is statistical and the second is systematic. Finally, a sample of [Formula: see text] decays is used to derive the ratios of branching fractions [Formula: see text] and [Formula: see text], where the third error corresponds to the uncertainty of the branching fraction of [Formula: see text] 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".