Bibliographic record
Abstract
Fundamental research in physics aims to answer questions about the nature of the Universe. Particle physics focuses on the fundamental forces and building blocks of matter. The best model to date is the Standard Model (SM) of particle physics. According to the Standard Model, the Universe is composed of particles that make up matter — quarks and leptons — and particles that carry the interactions between them. One of the quarks, called a beauty quark b, is the focus of this dissertation. Investigating the decays of the beauty quark can provide an insight into physics beyond the SM. In particular, this research focuses on the b→sll transition. According to the SM, this process is very rare, making it easier to observe potential contributions from new physics, even if they are small. The decay of interest in this search is B→K*ee. The analysis is performed by fitting an angular function to the distributions of the decay angles and comparing the best-fit parameters with SM predictions. To ensure reliable results, the angular analysis is performed first using a ''control channel'': a decay that results in the same particles but is well known and agrees with the Standard Model predictions. In this analysis, the control decay is B→K*J/ψ(→ee). An angular analysis of this decay is the main topic of this thesis.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.033 | 0.007 |
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".