Evaluation of a Charge Readout Pad Scheme for Next Enriched Xenon Observatory
Bibliographic record
Abstract
The neutrinos are fundamental particles.They are amongst the most difficult particle to detect due to their properties.The existence of the neutrinos has been known for the last several decades, yet their masses still have not been measured by experiments.The Enriched Xenon Observatory, EXO, is one of the experiment attempting to probe the masses of the neutrinos by observing the ultra rare neutrinoless double beta decay of 136 Xe.The EXO-200 detector uses a liquid xenon filled time projection chamber (TPC) to achieve high sensitivity measurements.The work presented here focuses on the development of a new charge readout scheme.A small gas TPC was built to test a series of charge readout pad structure.This detector measures the ionization signals (direct and induction) produced from the gas ionization by an alpha source emitter.The signals are read out with a commercial data acquisition system and a model is fitted to the data.The data analysis will demonstrate some of the challenges faced in the operation and modelling of this readout pad system.Even with the difficulties encountered, energy resolution and angular distribution results provide guidance for the collaboration for the future of this type of charge readout scheme.I would like to first show my appreciation to my supervisor, Dr. Kevin Graham, for taking me as a student, supporting and guiding me during the work of this thesis.I also want to show my appreciation to Dr. Caio Licciardi for all the valuable advices and help with the analysis.I also say thank you to Dr. David Sinclair for the many discussions we had along the way
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".