Global analysis of π<sup>±</sup> and K<sup>±</sup> fragmentation functions and their application to top quark decays considering new BABAR and Belle experimental data
Bibliographic record
Abstract
Recently, the Belle and BABAR collaborations published the single-inclusive electron–positron annihilation data at the center of mass energies ([Formula: see text]) of 10.52 and 10.54 GeV, respectively. These new data offer one the possibility to determine the nonperturbative initial conditions of fragmentation functions (FFs) much more accurately. Here, we extract the FFs of π± and K± particles at next-to-leading order (NLO) including these new data, which are in the regions of larger scaled-energy z and lower [Formula: see text]. However, the π± and K± FFs were calculated previously, but our new analysis shows that adding these new data, for instance, changes the (u, s) → π+ FFs in the large-z region while the s → π+ FF is also changed at low z. These new data also change the u → K+ FF at low z (z < 0.2) more than at large z, but the d → K+ FF is affected at z > 0.07. The FF of g → K+ is decreased everywhere, for example, about 25% at z = 0.01. We also apply, for the first time, the extracted FFs to make our predictions for the scaled-energy distributions of π± and K± inclusively produced in top quark decays at NLO.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".