Bibliographic record
Abstract
SNO+ is a multipurpose detector situated at the SNOLAB facility located at Creighton mine 2 km deep. The SNO+ experiment will have three phases: water, pure scintillator and Te-loaded scintillator. With the detector filled with scintillator, solar neutrinos, geo and reactor anti-neutrinos, and supernova neutrinos can be studied. To analyze the data collected by the detector, it is important to have detailed knowledge of the detector response. This is why calibration is a crucial part of the experiment. The detector response to neutrons will allow us to study the anti-neutrino flux coming from reactors in Canada. Anti-neutrinos can be detected via the inverse beta decay reaction which can be tagged using the neutrons it produces. This thesis will discuss the radioactive calibration source Americium Beryllium (AmBe) which produces neutrons and gammas. The existing AmBe source - inherited from the SNO experiment - that will be used in water phase has to be modified for the scintillator and loaded scintillator phases. Simulations were carried out to determine the optimal additional shielding required for the scintillator phase. The optimal shielding was determined to be 2 mm of lead surrounded by 1 mm of stainless steel for the encapsulation. The new design for the AmBe source was finalised. The estimated neutron capture event detection efficiency is 74.22%. The analysis of the source deployment at various positions within the detector and the shadowing effects are discussed as well.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".