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Record W2245372074 · doi:10.1109/ted.2015.2508672

Characterization of Lag Signal in Amorphous Selenium Detectors

2016· article· en· W2245372074 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Electron Devices · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Semiconductor Detectors and Materials
Canadian institutionsConcordia UniversityUniversity of Waterloo
Fundersnot available
KeywordsPhotocurrentDetectorSIGNAL (programming language)Intensity (physics)Materials scienceLight intensityLagOptoelectronicsElectric fieldOpticsCurrent (fluid)ResidualPhysicsMathematicsComputer science

Abstract

fetched live from OpenAlex

The photocurrent and the lag signals in amorphous selenium (a-Se) detectors have been characterized by measuring the optical and residual currents under varying light intensity, applied electric field, and temperature. A mathematical model for the transient photocurrent and residual current in a-Se detectors has also been developed. The photocurrent and the lag signal increase rapidly with the applied field because of enhancement of the quantum yield. The residual current increases with increasing the field, ambient temperature, and light intensity. The lag signal gets saturated with increasing the intensity. The percentage lag signal decreases with increasing the field and light intensity.

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.

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 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 score0.069
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

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 science0.0000.000
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 head0.007
GPT teacher head0.206
Teacher spread0.198 · 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