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Record W2104907746 · doi:10.1109/nssmic.1998.773817

An APD-based quad scintillator detector module with pulse shape discrimination coding for PET

2002· article· en· W2104907746 on OpenAlexaff
Roger Lecomte, A. Saoudi, D. Rouleau, H. Dautet, D. A. Waechter, M. Andreaco, M. Casey, Lars Eriksson, R. Nutt

Bibliographic record

Venue1998 IEEE Nuclear Science Symposium Conference Record. 1998 IEEE Nuclear Science Symposium and Medical Imaging Conference (Cat. No.98CH36255) · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsScintillatorAvalanche photodiodeOpticsDetectorScintillationPhysicsPhotodetectorPhotodiodePixelOptoelectronicsScintillation counterEnergy (signal processing)Noise (video)Computer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

A detector module allowing individual crystal identification without analog coding is proposed. The basic cell is made of a 2/spl times/2 array of scintillators having different decay times that can be identified by pulse shape discrimination. A 16 pixel module consisting of a 2/spl times/2 array of these quad scintillator cells coupled to a 2/spl times/2 avalanche photodiode (APD) array was assembled and tested. In this design, the signal-to-noise ratio can be optimized in two ways: (a) the electronic noise in individual APD channels is minimized by avoiding light sharing between photodetectors; (b) light collection efficiency is improved by eliminating light septa within cells to allow scintillation light propagation across crystals. All four crystals in a BGO/LSO/YSO/CsI(T1) assembly can be clearly separated and individually gated for energy. An energy resolution better than 13% can be obtained in all pixels for 511 keV gamma-rays.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0030.007
Scholarly communication0.0030.004
Open science0.0030.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.253
Teacher spread0.238 · 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; both teacher heads agree on what is shown here.

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

Citations12
Published2002
Admission routes1
Has abstractyes

Explore more

Same venue1998 IEEE Nuclear Science Symposium Conference Record. 1998 IEEE Nuclear Science Symposium and Medical Imaging Conference (Cat. No.98CH36255)Same topicRadiation Detection and Scintillator TechnologiesFrench-language works237,207