Event-by-Event Direction Reconstruction of Solar Neutrinos in a High Light-Yield Liquid Scintillator
Bibliographic record
Abstract
Parallel Talk presented at the XX International Workshop on Neutrino Telescopes - Venice 23-27 October 2023 Abstract: SNO+ is a large multipurpose experiment located in the SNOLAB underground laboratory in Sudbury, Canada. With an extensive physics programme focused on many neutrino physics topics and nucleon decay searches, the ultimate goal of SNO+ is the search for the neutrinoless double beta decay of 130Te. After a commissioning phase with water as the target medium, whose data allowed measurements of solar neutrinos and the detection of reactor antineutrinos, SNO+ is now filled with 780 tonnes of liquid scintillator. The higher light yield of the scintillator enhances the physics capabilities of the experiment, and the physics programincluding reactor, geo and solar neutrinos is underway. The data is also being used to quantify backgrounds and understand the detector response in preparation for the neutrinoless double beta decay search, when the scintillator is loaded with tellurium at 0.5% by weight. This talk will highlight the recent results of the SNO+ experiment and discuss the prospects for the neutrinoless double beta decay searches.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".