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Record W4401633160 · doi:10.22215/etd/2024-16125

A Search for 134Xe Double Beta Decay with EXO-200 detector

2024· dissertation· en· W4401633160 on OpenAlexaff
Allan Felipe Nunes Perna

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsCarleton University
Fundersnot available
KeywordsDouble beta decayNeutrinoNuclear physicsDetectorPhysicsBeta decayPhase (matter)Energy (signal processing)Particle physicsParticle (ecology)OpticsQuantum mechanics

Abstract

fetched live from OpenAlex

This master's thesis presents a study of the rare two-neutrino double beta decay (2νββ) of 134 Xe using data from the EXO-200 experiment.The EXO-200 experiment, located at the Waste Isolation Pilot Plant (WIPP) in the United States, is a low-background experiment designed to search for neutrinoless double beta decay (0νββ) using liquid xenon enriched in 136 Xe.However, the EXO-200 experiment also provides an opportunity to study the 2νββ decay of 134 Xe due to its higher concentration (19.1% of its mass is 134 Xe), which is two times larger than that found in nature.The EXO-200 experiment collected data in two phases: Phase I (September 2011 -February 2014) and Phase II (January 2016 -December 2018).This thesis analyzes Phase II data, which is expected to yield better results than Phase I due to detector enhancements.The analysis utilized the energy, topology, and position of particle interactions in the detector to discriminate between signal and background events.The study was extended to several lower energy thresholds to increase detection efficiency.Using the Phase II dataset (exposure: 28.6 kg•yr), the 90% Confidence Level lower limit for the 134 Xe 2νββ half-life is T 2νββ 1/2 > 2.7 × 10 21 yr.This result, while not exceeding the initial Phase II year's result due to energy threshold limitations, is about three times larger than Phase I's.i

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.027
GPT teacher head0.342
Teacher spread0.315 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2024
Admission routes1
Has abstractyes

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