Cosmogenic-neutron activation of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>TeO</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:math>and implications for neutrinoless double-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>β</mml:mi></mml:math>decay experiments
Bibliographic record
Abstract
Flux-averaged cross sections for cosmogenic-neutron activation of natural tellurium were measured using a neutron beam containing neutrons of kinetic energies up to $\ensuremath{\sim}800$ MeV and having an energy spectrum similar to that of cosmic-ray neutrons at sea level. Analysis of the radioisotopes produced reveals that $^{110\mathrm{m}}\mathrm{Ag}$ will be a dominant contributor to the cosmogenic-activation background in experiments searching for neutrinoless double-$\ensuremath{\beta}$ decay of $^{130}\mathrm{Te}$, such as the Cryogenic Underground Observatory for Rare Events (CUORE) and the Sudbury Neutrino Observatory Plus $(\mathrm{SNO}+)$. An estimate of the cosmogenic-activation background in the CUORE experiment has been obtained using the results of this measurement and cross-section measurements of proton activation of tellurium. Additionally, the measured cross sections in this work are also compared with results from semiempirical cross-section calculations.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".