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Record W2528554296 · doi:10.1109/ted.2017.2671365

a-Si:H TFT-Silicon Hybrid Low-Energy X-Ray Detector

2017· article· en· W2528554296 on OpenAlexafffund
Kyung-Wook Shin, Karim S. Karim

Bibliographic record

VenueIEEE Transactions on Electron Devices · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsSiliconThin-film transistorDetectorX-ray detectorAmorphous siliconOptoelectronicsPixelTransistorDiffractionImage resolutionMaterials scienceOpticsPhotonPhysicsCrystalline siliconNanotechnologyVoltage

Abstract

fetched live from OpenAlex

Direct conversion crystalline silicon X-ray imagers are used for low-energy X-ray photon (4-20 keV) detection in scientific research applications such as protein crystallography. In this paper, we demonstrate a novel pixel architecture that integrates a crystalline silicon X-ray detector with a thin-film transistor amorphous silicon pixel readout circuit. We describe a simplified two-mask process to fabricate a complete imaging array and present preliminary results that show the fabricated pixel to be sensitive to 5.89-keV photons from a low activity Fe-55 gamma source. This paper presented can expedite the development of high spatial resolution, low cost, direct conversion imagers for X-ray diffraction and crystallography applications.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.266
Teacher spread0.257 · 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

Citations5
Published2017
Admission routes2
Has abstractyes

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