Extraction of Active and Sterile Neutrino Mixing Parameters with the Sudbury Neutrino Observatory
Bibliographic record
Abstract
The Sudbury Neutrino Observatory (SNO) is a 1 kilotonne heavy-water Čerenkov detector designed to study fundamental properties of neutrinos produced by thermonuclear fusion reactions in the core of the Sun. The uniqueness of SNO resides in its capability to distinctively measure the total flux of all active neutrino flavours as well as the flux of electron neutrinos, through the Neutral-Current (NC) and Charged-Current (CC) interactions of neutrinos on deuterium, respectively. The measurements of the NC and CC fluxes for neutrinos originated from 8B disintegration inside the Sun unambiguously proved that neutrinos change their flavour while traveling to the Earth. These results are consistent with predictions from a neutrino oscillation hypothesis on neutrino flavour transitions due to the mixing of massive neutrino states. The NC measurement from SNO also solved the long-standing Solar Neutrino Problem (SNP). In this dissertation, the measurements of the fundamental properties of neutrinos, in particular their mixing parameters, are presented. Data samples from SNO and other experiments are used to extract the mixing parameters of active
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".