Observation of the $$ {K}^{+}\to {\pi}^{+}\nu \overline{\nu} $$ decay and measurement of its branching ratio
Bibliographic record
Abstract
A bstract A measurement of the $$ {K}^{+}\to {\pi}^{+}\nu \overline{\nu} $$ K + → π + ν ν ¯ decay by the NA62 experiment at the CERN SPS is presented, using data collected in 2021 and 2022. This dataset was recorded, after modifications to the beamline and detectors, at a higher instantaneous beam intensity with respect to the 2016–2018 data taking. Combining NA62 data collected in 2016–2022, a measurement of $$ \mathcal{B}\left({K}^{+}\to {\pi}^{+}\nu \overline{\nu}\right)=\left({13.0}_{-3.0}^{+3.3}\right)\times {10}^{-11} $$ B K + → π + ν ν ¯ = 13.0 − 3.0 + 3.3 × 10 − 11 is reported. With 51 signal candidates observed and an expected background of $$ {18}_{-2}^{+3} $$ 18 − 2 + 3 events, $$ \mathcal{B}\left({K}^{+}\to {\pi}^{+}\nu \overline{\nu}\right) $$ B K + → π + ν ν ¯ becomes the smallest branching ratio measured with a signal significance above 5 σ .
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".