Robust Signal Extraction Methods and Monte Carlo Sensitivity Studies for the Sudbury Neutrino Observatory and SNO+ Experiments
Bibliographic record
Abstract
The third and final phase of the Sudbury Neutrino Observatory (SNO) experiment utilized a series of 3 He proportional counters called Neutral Current Detectors (NCDs) to detect the neutrons produced by the neutral current interactions of solar neutrinos in the detector. The number of neutrons detected by the NCDs, and hence the total flux of 8 B solar neutrinos, has been determined using two novel signal extraction techniques which were designed to be robust against potential unexpected behaviour in the NCD background. These techniques yield total 8 B solar neutrino flux measurements of 5.04 +0.42 −0.40 (stat) ± 0.28(syst)x106 cm −2 s −1 and (4.40 − 6.43)x10 6 cm −2 s −1, which are in good agreement with previous SNO results and with solar model predictions, and which confirm that previous NCD analyses were not unduly affected by unexpected background behaviour. The majority of the hardware from the now-completed SNO experiment will be reused to create a new liquid scintillator based neutrino experiment called SNO+. An important part of the SNO+ physics program will be a search for neutrinoless double beta decay, carried out by dissolving 150 Nd into the scintillator. The sensitivity of the SNO+ experiment to neutrinoless double beta decay
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".