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Record W1966472543 · doi:10.1109/nssmic.2012.6551315

Study of the transient response of PI/a-Se photodetectors for indirect conversion medical imaging

2012· article· en· W1966472543 on OpenAlexaff
Shiva Abbaszadeh, Nicholas Allec, Karim S. Karim

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Semiconductor Detectors and Materials
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPhotodetectorOptoelectronicsMaterials scienceDetectorDark currentX-ray detectorQuantum efficiencyElectrodeOpticsPolyimideElectric fieldImage sensorFabricationTransient responseLayer (electronics)PhysicsElectrical engineeringNanotechnology

Abstract

fetched live from OpenAlex

Previously two different amorphous selenium (a-Se) photodetector designs were proposed for indirect conversion medical imaging using polyimide (PI) as blocking contacts: a lateral comb structure where a PI layer covers both electrodes and a vertical structure where a PI layer is placed between the positively biased electrode and a-Se. These detectors have raised interest due to their simple structure, ease of fabrication, very low dark current at high electric fields, and high quantum efficiency. In this study we examine the transient behavior of these detectors for fluoroscopic or tomographic applications. The photo response to a short light pulse (10-100 μs) is examined in both structures. The presence of charge accumulation at the PI/a-Se interface is investigated by observing the photo response of consecutive light pulses under different electric fields. This work demonstrates the promise of low-cost a-Se devices for use in indirect conversion large area digital medical X-ray imaging applications such as real-time fluoroscopy and computed tomography.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.259

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.019
GPT teacher head0.261
Teacher spread0.242 · 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 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

Citations1
Published2012
Admission routes1
Has abstractyes

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