sno+ background study: polonium on acrylic vessel surface and radon assay
Bibliographic record
Abstract
SNO+ is a 780 tonnes organic liquid scintillator neutrino detector located at Vale’s Creighton mine, Sudbury, ON. 2 km overburden of rock above helps to achieve the low cosmic radiation background level of SNO+. Meanwhile, radioactive material in the rock can decay and produce radiation in the region of interest for the search of 0νββ decay. SNO+ is looking for neutrinos at very low energy and thus it is crucial to have a low background environment. My thesis evaluates two kinds of background sources: 222Rn and 210Po. 222Rn is the progeny of 238U in the rock. The water and gas assays are used to monitor the 222Rn concentration in the surrounding cavity water and other parts of the experiment or other gas volumes in SNOLAB. The analysis of the SNO+ data helps to understand the 210Po activity on the internal surface of the detector’s acrylic vessel. The 222Rn level in the cavity water is below the target of 4.5 × 10−13 gU238/gH2O. The Rn levels in the LN2 plant and international dewar are at a 10−4 reduction factor compared to mine air. The 210Po background level in the internal AV is holding a relatively constant level of about 1800 events per second. Spatially, the 210Po backgrounds are more active at the equator and the belly plate regions. The estimated number of 210Pb atoms deposited on the AV inner surface is 1.84 × 1012 .
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".