Constraints on the minimal supergravity parameter space from NLO calculation of isospin asymmetry in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>B</mml:mi><mml:mo>→</mml:mo><mml:msup><mml:mi>K</mml:mi><mml:mo>*</mml:mo></mml:msup><mml:mi>γ</mml:mi></mml:math>
Bibliographic record
Abstract
The contributions of supersymmetric particles in the isospin symmetry violation in $B\ensuremath{\rightarrow}{K}^{*}\ensuremath{\gamma}$ decay mode are investigated. The model parameters are adopted from minimal Supergravity with minimal flavor violation. A complete scan of the mSUGRA parameter space has been performed, using the next to leading supersymmetric contributions to the relevant Wilson coefficients. The results are compared to recent experimental data in order to obtain constraints on the parameter space. We point out that isospin asymmetry can prove to be an interesting observable and imposes severe restrictions on the allowed parameter space, in particular, for large values of $\mathrm{tan}\ensuremath{\beta}$. The constraints obtained with isospin asymmetry also appear as more restricting than the ones from the branching ratio of $B\ensuremath{\rightarrow}{X}_{s}\ensuremath{\gamma}$.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".