First measurement of radioactive isotope production through cosmic-ray muon spallation in Super-Kamiokande IV
Bibliographic record
Abstract
Cosmic-ray-muon spallation-induced radioactive isotopes with $\ensuremath{\beta}$ decays are one of the major backgrounds for solar, reactor, and supernova relic neutrino experiments. Unlike in scintillator, production yields for cosmogenic backgrounds in water have not been exclusively measured before, yet they are becoming more and more important in next generation neutrino experiments designed to search for rare signals. We have analyzed the low-energy trigger data collected at Super-Kamiokande IV in order to determine the production rates of $^{12}\mathrm{B}$, $^{12}\mathrm{N}$, $^{16}\mathrm{N}$, $^{11}\mathrm{Be}$, $^{9}\mathrm{Li}$, $^{8}\mathrm{He}$, $^{9}\mathrm{C}$, $^{8}\mathrm{Li}$, $^{8}\mathrm{B}$, and $^{15}\mathrm{C}$. These rates were extracted from fits to time differences between parent muons and subsequent daughter $\ensuremath{\beta}$'s by fixing the known isotope lifetimes. Since $^{9}\mathrm{Li}$ can fake an inverse-beta-decay reaction chain via a $\ensuremath{\beta}+n$ cascade decay, producing an irreducible background with detected energy up to a dozen MeV, a dedicated study is needed for evaluating its impact on future measurements; the application of a neutron tagging technique using correlated triggers was found to improve this $^{9}\mathrm{Li}$ measurement. The measured yields were generally found to be comparable with theoretical calculations, except the cases of the isotopes $^{8}\mathrm{Li}/^{8}\mathrm{B}$ and $^{9}\mathrm{Li}$.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".