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Measurement of radioactive contamination in the CCD’s of the DAMIC experiment

2016· article· en· W2418143549 on OpenAlexaff
A. A. Aguilar-Arevalo, D. Amidei, X. Bertou, D G Bole, Melissa Butner, Gustavo Cancelo, Angélica Vásquez-Grandón, Á. Chavarría, Simon Dixon, Juan Carlos D’Olivo, Juan Estrada, Guillermo Fernández Moroni, K. Torres, Federico Izraelevitch, A. Kavner, B. Kilminster, Ian T. Lawson, J. Liao, M. Miralles Lopez, Jorge Molina, G. Moreno-Granados, J. Pena, P. Privitera, Y. Sarkis, V. Scarpine, T. Schwarz, M. Sofo Haro, Javier Tiffenberg, D. Torres Machado, Frédéric Trillaud, X Yol, Jing Zhou

Bibliographic record

VenueJournal of Physics Conference Series · 2016
Typearticle
Languageen
FieldEngineering
TopicCCD and CMOS Imaging Sensors
Canadian institutionsSnolab
Fundersnot available
KeywordsWIMPUraniumContaminationPhysicsSiliconSemiconductor detectorDetectorDark matterThoriumNuclear physicsRadonRadiochemistryChemistryOpticsOptoelectronicsParticle physics

Abstract

fetched live from OpenAlex

DAMIC (Dark Matter in CCDs) is an experiment searching for dark matter particles employing fully-depleted charge-coupled devices. Using the bulk silicon which composes the detector as target, we expect to observe coherent WIMP-nucleus elastic scattering. Although located in the SNOLAB laboratory, 2 km below the surface, the CCDs are not completely free of radioactive contamination, in particular coming from radon daughters or from the detector itself. We present novel techniques for the measurement of the radioactive contamination in the bulk silicon and on the surface of DAMIC CCDs. Limits on the Uranium and Thorium contamination as well as on the cosmogenic isotope 32 Si, intrinsically present on the detector, were performed. We have obtained upper limits on the 238 TJ (232 Th) decay rate of 5 (15) kg_1 d_1 at 95% CL. Pairs of spatially correlated electron tracks expected from 32 Si-32 P and 210 Pb-210 Bi beta decays were also measured. We have found a decay rate of 80+l10 -65 kg_1 d_1 for 32 Si and an upper limit of - 35 kg-1 d-1 for 210 Pb, both at 95% CL.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.129

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)0.0000.000

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 head0.021
GPT teacher head0.220
Teacher spread0.200 · 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.

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

Citations2
Published2016
Admission routes1
Has abstractyes

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