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Development, characterization and production of a novel water-based liquid scintillator based on the Surfactant TRITON™ X-100

2024· article· en· W4402274744 on OpenAlexaff
Hans Steiger, Manuel Böhles, Matthias Raphael Stock, David Dörflinger, Ulrike Fahrendholz, Anastasia Mpoukouvalas, Lothar Oberauer, Andreas Steiger, Dorina Zundel

Bibliographic record

VenueJournal of Instrumentation · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsScintillatorPulmonary surfactantCharacterization (materials science)Materials scienceProduction (economics)Environmental sciencePhysicsNanotechnologyOpticsDetector

Abstract

fetched live from OpenAlex

Abstract Water-based Liquid Scintillator (WbLS) is a novel detector medium for particle physics experiments. Applications range from the use as hybrid Cherenkov/scintillation target in low-energy and accelerator neutrino experiments to large-volume neutron vetoes for dark matter detectors. Here we present a WbLS based on well-known components (the surfactant Triton-X, the fluor PPO and vitamin C for long-term stability), with which a new recipe was developed and the result subjected to a thorough characterization of its properties. In addition, based on neutron scattering data we are able to demonstrate that the pulse shape discrimination capabilities of this particular LS are comparable to all-organic LAB based scintillators.

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 score0.059
Threshold uncertainty score0.205

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 head0.019
GPT teacher head0.249
Teacher spread0.229 · 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

Citations8
Published2024
Admission routes1
Has abstractyes

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