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Polyethylene naphthalate film as a wavelength shifter in liquid argon detectors

2019· article· en· W2805400680 on OpenAlexafffund

Bibliographic record

VenueThe European Physical Journal C · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsCarleton UniversityQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsScintillationArgonContext (archaeology)SpectrometerDetectorKaptonPolyethylene naphthalateIsotopologueWavelength

Abstract

fetched live from OpenAlex

Liquid argon-based scintillation detectors are important for dark matter searches and neutrino physics. Argon scintillation light is in the vacuum ultraviolet region, making it hard to be detected by conventional means. Polyethylene naphthalate (PEN), an optically transparent thermoplastic polyester commercially available as large area sheets or rolls, is proposed as an alternative wavelength shifter to the commonly-used tetraphenyl butadiene (TPB). By combining the existing literature data and spectrometer measurements relative to TPB, we conclude that the fluorescence yield and timing of both materials may be very close. The evidence collected suggests that PEN is a suitable replacement for TPB in liquid argon neutrino detectors, and is also a promising candidate for dark matter detectors. Advantages of PEN are discussed in the context of scaling-up existing technologies to the next generation of very large ktonne-scale detectors. Its simplicity has a potential to facilitate such scale-ups, revolutionizing the field.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.007
GPT teacher head0.221
Teacher spread0.214 · 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

Citations30
Published2019
Admission routes2
Has abstractyes

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