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Record W4322489008 · doi:10.24124/2022/59366

Improving the energy and time resolution of the DRAGON array

2022· dissertation· en· W4322489008 on OpenAlexaff
William C. Huang

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDetectorPhysicsResolution (logic)Energy (signal processing)Gamma rayOpticsNuclear physicsComputer science

Abstract

fetched live from OpenAlex

DRAGON seeks to replace its BGO detectors with LaBr3:Ce detectors. The Geant4 simulation estimates gamma ray capture efficiency values of 3.384±0.011% and 1.113±0.007% for the BGO detector and the LaBr3:Ce detector, respectively for 0.6617 MeV gamma rays at 5 cm distance. The latter achieves an experimental efficiency of 1.102±0.042% and an experimental energy resolution of 3.282±0.036% for these gamma rays. The experimental and simulated LaBr3:Ce detector efficiency results agree within error. However, the simulation may overestimate the detector efficiency at high gamma ray energies, as observed at 4.44 MeV and 6.131 MeV. Furthermore, the timing method is performed to utilize its high time resolution. The average resonance energy is 0.47428±0.00815 MeV/u which agrees with the true value of 0.475 MeV/u. Therefore, the energy and time resolution of the LaBr3:Ce detector improve DRAGON’S ability to study radiative capture reactions, with its lower efficiency being its only drawback.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.004
GPT teacher head0.202
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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