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Record W2020264811 · doi:10.1117/12.813886

Characterization of current programmed amorphous silicon active pixel sensor readout circuit for dual mode diagnostic digital x-ray imaging

2009· article· en· W2020264811 on OpenAlexaff
N. Safavian, Mohammad Y. Yazdandoost, Dongliang Wu, Afrin Sultana, Mohammad Hadi Izadi, K. S. Karim, Arokia Nathan, J. A. Rowlands

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsLakehead UniversityThunder Bay Regional Research InstituteUniversity of Waterloo
Fundersnot available
KeywordsThin-film transistorPixelOptoelectronicsTransistorCapacitorCapacitanceMaterials scienceImage sensorThreshold voltageAmorphous siliconVoltageSiliconOpticsPhysicsCrystalline siliconNanotechnologyElectrode

Abstract

fetched live from OpenAlex

A dual mode current-programmed, current-output active pixel sensor (DCAPS) in amorphous silicon (a-Si:H) technology is introduced for digital X-ray imaging, and in particular, for hybrid fluoroscopic and radiographic imagers. Here, each pixel includes an extra capacitor that selectively is coupled to the pixel capacitance to realize the dual mode behavior. Pixel structure, operation and characteristics are presented. The proposed DCAPS circuit was fabricated and assembled using an in-house bottom gate inverted staggered a-Si:H thin film transistor (TFT) process. Gain, lifetime, transient performance as well as noise analysis were carried out. The results are promising and demonstrate that the DCAPS enables dual mode X-ray imaging while compensating for the long term electrical and thermal stress related a-Si TFT threshold voltage (V<sub>t</sub>) shift.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.110
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.012
GPT teacher head0.224
Teacher spread0.212 · 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.

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

Citations0
Published2009
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicThin-Film Transistor TechnologiesFrench-language works237,207