Measurement of muon annual modulation and muon-induced phosphorescence in NaI(Tl) crystals with DM-Ice17
Bibliographic record
Abstract
We report the measurement of muons and muon-induced phosphorescence in DM-Ice17, a NaI(Tl) direct detection dark matter experiment at the South Pole. Muon interactions in the crystal are identified by their observed pulse shape and large energy depositions. The measured muon rate in DM-Ice17 is $2.93\ifmmode\pm\else\textpm\fi{}0.04\text{ }\text{ }\ensuremath{\mu}/\text{crystal}/\text{day}$ with a modulation amplitude of $12.3\ifmmode\pm\else\textpm\fi{}1.7%$, consistent with expectation. Following muon interactions, we observe long-lived phosphorescence in the NaI(Tl) crystals with a decay time of $5.5\ifmmode\pm\else\textpm\fi{}0.5\text{ }\text{ }\mathrm{s}$. The prompt energy deposited by a muon is correlated to the amount of delayed phosphorescence, the brightest of which consist of tens of millions of photons. These photons are distributed over tens of seconds with a rate and arrival timing that do not mimic a scintillation signal above $2\text{ }\text{ }{\mathrm{keV}}_{\mathrm{ee}}$. While the properties of phosphorescence vary among individual crystals, the annually modulating signal observed by DAMA cannot be accounted for by phosphorescence with the characteristics observed in DM-Ice17.
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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 | 0.000 | 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".