Optical Calibration of the SNO+ Detector using Internal Backgrounds
Bibliographic record
Abstract
The SNO+ experiment is a multi-purpose neutrino detector located 2 km underground at SNOLAB in Sudbury, Ontario. The primary goal of the experiment is to search for neutrinoless double beta decay in tellurium-130. An observation of neutrinoless double beta decay would demonstrate the Majorana nature of neutrinos. In order to detect such a rare decay process, a precise optical calibration of the target medium is critical. A typical calibration campaign consists of a series of in-situ deployments of a quasi-isotropic light diffusing sphere (a.k.a. "laserball"). The laserball is positioned at multiple points within the detector and pulsed over a period of time at a fixed set of wavelengths, allowing the photomultiplier tube responses and attenuations of the three detector media (scintillator, acrylic and ultra-pure water) to be extracted via an optical model. This thesis presents a method to extract an effective attenuation length of the scintillator by replacing the laserball with a ball of reconstructed background events. Utilizing the intrinsic radioactivity of the detector as the calibration source provides a non-invasive approach to monitor changes in optical attenuation as the detector state evolves over time.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".