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Record W4240886342 · doi:10.22215/etd/2019-13705

Low-Energy Threshold Analysis Using the DEAP-3600 Dark Matter Detector

2019· dissertation· en· W4240886342 on OpenAlexaff
Jesse Lock

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsCarleton University
Fundersnot available
KeywordsWIMPPhysicsDark matterWeakly interacting massive particlesCherenkov radiationDetectorNuclear physicsParticle physicsAstronomyDark energyScalar field dark matterOpticsCosmology

Abstract

fetched live from OpenAlex

DEAP-3600 is a single-phase liquid argon WIMP detector located 2 km underground in the SNOLAB research facility.DEAP-3600 is searching for dark matter; an elusive form of matter that was first postulated in the early 20 th century, but has not yet been found.The goal of the following work is to perform a low mass WIMP search.A low mass WIMP search is made possible by lowering the energy threshold of the hardware trigger from 1000 ADC to 150 ADC.Low energy events in the detector are characterized as Cherenkov radiation, low energy retriggers, or high energy retriggers; all of which are background events.The final data set has a live time of 2.10 days and an exposure of 4.41 × 10 3 kg • days using a LAr target mass of (3279±97)kg.The results from the low mass WIMP search is a WIMP-nucleon spin independent cross-section of 3.96 × 10 -42 cm 2 at a 90% CL corresponding to WIMPs with a mass of 55 GeV/c 2 .

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.004

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.

Opus teacher head0.008
GPT teacher head0.236
Teacher spread0.228 · 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 designObservational
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
Published2019
Admission routes1
Has abstractyes

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