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Record W4401991125 · doi:10.1109/tns.2024.3451618

On the Applicability of <sup>48</sup>V in Positron Annihilation Lifetime Spectroscopy

2024· article· en· W4401991125 on OpenAlexfundno aff
Mircea Lechintan, N. Djourelov

Bibliographic record

VenueIEEE Transactions on Nuclear Science · 2024
Typearticle
Languageen
FieldEngineering
TopicMuon and positron interactions and applications
Canadian institutionsnot available
FundersOntario Ministry of Research and Innovation
KeywordsNuclear physicsAnnihilationPositronSpectroscopyPhysicsAtomic physicsPositron Lifetime SpectroscopyGamma spectroscopyPositron annihilationElectron

Abstract

fetched live from OpenAlex

The applicability of the 48V isotope as a source of positrons for positron annihilation lifetime spectroscopy (PALS) measurements is discussed. It has been demonstrated that using such a positron source, the classical PALS setup with two detectors does not accurately determine the positron annihilation parameters of the samples being studied. This issue arises when one of the two nuclear gamma rays (of energies of 983 and 1312 keV) that are emitted almost simultaneously with the creation of a positron triggers a start signal, while the other nuclear gamma triggers a stop signal instead of the 511-keV annihilation quanta. These events manifest as prompt coincidences in the start-stop histogram, rendering the analysis of PALS spectra unreliable. To address this problem, a modification to the classical PALS spectrometer was proposed and tested. This modification involved incorporating a logic branch that significantly reduced the undesired prompt coincidences between the 983- and 1312-keV gamma rays. By conducting measurements on a series of samples utilizing 2- and 25-<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> m-thick Ti foils enriched with 48V, it was demonstrated that the altered setup reliably extracts accurate information on the positron annihilation states within the samples being examined.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.239
Teacher spread0.233 · 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 designSimulation or modeling
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

Citations1
Published2024
Admission routes1
Has abstractyes

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