Silicon detector testing for neutron beta decay experiment nab
Bibliographic record
Abstract
The Standard Model of Particle Physics is a successful yet incomplete description of matter and interactions in the universe. The rate of neutron beta decay in the decay of free neutrons is sensitive to beyond the standard model physics where the types of interactions are constrained by the Lorentz invariance of bi-linear covariants. Precision measurements of decay correlation parameters can be used to test standard model predictions. The Nab experiment at the spallation neutron source(SNS) Oakridge National Laboratory aims to measure the anti-electron-neutrino correlation \lq a\rq, and Fierz interference term \lq b\rq\:in unpolarized neutron decay to greater precision to date. The Nab collaboration uses large area silicon detectors to measure decay products in free neutron decay. Systematic tests of detector system properties are necessary for any precision detection system. The University of Manitoba group modified the Manitoba 2 mass spectrometer to operate as a low energy proton source to use as a detector test facility for low energy protons. The full Nab detector apparatus was installed and tested at the University of Manitoba in early 2021. The subject of this thesis is the preparation of the Manitoba 2 proton source for detector testing and, the operation and characterization of the Nab detector for 30 keV energy protons. In this work, the corresponding setup, tests and partial measurement results are presented. The measured proton energy in general may depend on detector temperature, radial location of detector pixel and the detector bias current, all of which were investigated. The proton energy was measured for three different accelerating potentials (25 KV, 30 KV, 35 KV). The proton event rate was measured in neighbouring pixel during the proton beam sweep across the pixel boundary.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".