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Record W2096428485 · doi:10.1109/tns.2009.2017193

The Effect of the Dielectric Layer Thickness on Spectral Performance of CdZnTe Frisch Collar Gamma Ray Spectrometers

2009· article· en· W2096428485 on OpenAlexaff
Alireza Kargar, Adam C. Brooks, Mark Harrison, K. T. Kohman, Rans B. Lowell, Roger C. Keyes, Henry Chen, Glenn Bindley, Douglas S. McGregor

Bibliographic record

VenueIEEE Transactions on Nuclear Science · 2009
Typearticle
Languageen
FieldEngineering
TopicAdvanced Semiconductor Detectors and Materials
Canadian institutionsRedlen Technologies (Canada)
Fundersnot available
KeywordsCollarDielectricPlanarMaterials scienceElectric fieldSpectrometerBar (unit)Layer (electronics)OpticsOptoelectronicsDetectorComposite materialPhysicsComputer scienceMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

The spectral performance as a function of the dielectric layer thickness for several CdZnTe Frisch collar devices was investigated. Seven different planar bar shaped detectors were fabricated from Redlen Technologies CdZnTe, and many Frisch collar devices were prepared from each planar device. The optimum dielectric layer thickness was experimentally determined for each device. The result of the optimal thickness study was verified through three-dimensional geometry modeling of the potential and electric field. It is shown that there exists an optimal dielectric layer thickness for best performance for CdZnTe Frisch collar devices with aspect ratios (L/W) greater than 2.5.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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

Citations11
Published2009
Admission routes1
Has abstractyes

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