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Record W2794300973

Characterization of Silicon Photomultiplier Readout Designs for Use in Positron Emission Tomography Systems

2011· article· en· W2794300973 on OpenAlexfundno aff
Chenyi Liu

Bibliographic record

VenueMspace (University of Manitoba) · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of ManitobaManitoba Health Research Council
KeywordsSilicon photomultiplierPositron emission tomographyCharacterization (materials science)PhotomultiplierPositronMaterials sciencePositron emissionOptoelectronicsPhysicsComputer scienceNanotechnologyOpticsNuclear physicsNuclear medicineScintillatorElectronMedicineDetector
DOInot available

Abstract

fetched live from OpenAlex

Geiger-mode avalanche photodiodes, or silicon photomultipliers, are promising light sensors for the next generation Positron Emission Tomography (PET) scanners. The sensor is being used in the scanner’s gamma ray detector to measure scintillation light. This thesis describes the test results of three gamma ray detectors that utilize silicon photomultipliers. The first one is a commercial detector, and the other two are custom made. The detectors are tested for their 511 keV photon energy and timing resolution, as well as their ability to measure light from small scintillator crystals. The two custom made detectors had smaller active area, but outperformed the commercial detector in energy resolution. The introduction of buffer amplifiers improved the timing resolution of one detector. All three detectors had their crystal decoding ability limited by signal multiplexing and the sensor’s dark noise. Finally, a detector design was proposed for the PET system being developed in our group.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.339

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 head0.034
GPT teacher head0.200
Teacher spread0.166 · 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 designObservational
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

Citations0
Published2011
Admission routes1
Has abstractyes

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