Bibliographic record
Abstract
The SNO+ experiment is located 2 km underground at SNOLAB in Sudbury, Canada. A low background search for neutrinoless double beta ($0\nu\beta\beta$) decay will be conducted using 780 tonnes of liquid scintillator loaded with 3.9 tonnes of natural tellurium, corresponding to 1.3 tonnes of $^{130}$Te. This paper provides a general overview of the SNO+ experiment, including detector design, construction of process plants, commissioning efforts, electronics upgrades, data acquisition systems, and calibration techniques. The SNO+ collaboration is reusing the acrylic vessel, PMT array, and electronics of the SNO detector, having made a number of experimental upgrades and essential adaptations for use with the liquid scintillator. With low backgrounds and a low energy threshold, the SNO+ collaboration will also pursue a rich physics program beyond the search for $0\nu\beta\beta$ decay, including studies of geo- and reactor antineutrinos, supernova and solar neutrinos, and exotic physics such as the search for invisible nucleon decay. The SNO+ approach to the search for $0\nu\beta\beta$ decay is scalable: a future phase with high $^{130}$Te-loading is envisioned to probe an effective Majorana mass in the inverted mass ordering region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.052 | 0.019 |
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".