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Record W2183165592 · doi:10.1002/pssc.201510129

Modeling of transient photocurrent in X‐ray detectors: application to a‐Se

2015· article· en· W2183165592 on OpenAlexafffund
Sinchita Siddiquee, M. Z. Kabir

Bibliographic record

VenuePhysica status solidi. C, Conferences and critical reviews/Physica status solidi. C, Current topics in solid state physics · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced X-ray and CT Imaging
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhotocurrentTransient (computer programming)ElectronDetectorX-ray detectorPhysicsOptoelectronicsCharge carrierMaterials scienceOpticsComputer scienceNuclear physics

Abstract

fetched live from OpenAlex

Abstract A mathematical model for transient photocurrent in X‐ray imaging detectors has been developed by considering charge carrier trapping under exponentially distributed carrier generation across the photoconductor. The model for the transient and steady‐state carrier distributions and hence the photocurrent has been developed by solving the carrier continuity equation for both holes and electrons. The model is applied to amorphous selenium (a‐Se) detectors for both chest radiography and mammography. We analyze the transient rise and decay of the photocurrent profile as a function of time. The quick rise and decay parts, and then the slow rise and decay parts of the photocurrent profile are due to the hole and electron transports, respectively. (© 2016 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.728
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.065
GPT teacher head0.362
Teacher spread0.297 · 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 designSimulation or modeling
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
Published2015
Admission routes2
Has abstractyes

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