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Record W2157841260 · doi:10.1109/nssmic.1997.672708

Testing scintillation transport models with photoelectron yields measured under different surface finishes

2002· article· en· W2157841260 on OpenAlexafffund
C. Moisan, Anthony Levin, H. Laman

Bibliographic record

Venue1997 IEEE Nuclear Science Symposium Conference Record · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsTRIUMF
FundersTRIUMF
KeywordsSurface roughnessSurface finishScintillationProfilometerMaterials scienceOpticsPhotonStylusScintillatorX-ray photoelectron spectroscopySurface (topology)Reflector (photography)PhysicsGeometryNuclear magnetic resonanceComposite materialDetectorAcoustics

Abstract

fetched live from OpenAlex

The UNIFIED, POLISH, and GROUND surface models of the optical photon transport program DETECT are tested for their capacity to predict the photoelectron yields measured with crystals of different surface finishes and reflective coats. Here, two BGO crystals of 5.6/spl times/12.8/spl times/29.7 mm, with respectively a polished and a corrugated surface finish are considered. Stylus profilometer scans are first taken to quantify their surface roughness. The crystals are then prepared in three different surface coat configurations to subsequently measure the photoelectron yield collected when they are excited by a beam of 511 keV photons. These measurements are used to confront the models' predictions on absolute ground. The results indicate that the transport of scintillation photons internally trapped within the volume of a highly polished crystal is well accounted for. However, significant discrepancies are noted between simulations and measurements when considering a corrugated finish or when the surface is coated by a diffuse reflector. Possible explanations are discussed and call for further investigations.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.221
Teacher spread0.180 · 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

Citations20
Published2002
Admission routes2
Has abstractyes

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