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Record W2135543891 · doi:10.1109/newcas.2006.250909

Low-Cost Stable a-Si:H AMOLED Display for Portable Applications

2006· article· en· W2135543891 on OpenAlexaff
G. Reza Chaji, Arokia Nathan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAMOLEDBackplaneOLEDActive matrixThin-film transistorMaterials scienceTransistorPower consumptionComputer scienceOptoelectronicsComputer hardwarePower (physics)Electrical engineeringNanotechnologyEngineering

Abstract

fetched live from OpenAlex

A large sector of display market comprises portable devices including cell phones, personal organizers, PDAs, portable electronic games, etc. Important design considerations for displays employed in these applications are power consumption and cost. Hydrogenated Amorphous silicon (a-Si:H) active matrix organic light emitting diode (AMOLED) displays are promising technology for these applications. However, the a-Si:H AMOLED backplane suffers from the temporal instability. Although, several stable driving schemes have been proposed, they suffer from high implementation cost due to extra driving circuitry and high power consumption due to additional operating cycles. This paper presents a new driving scheme that provides a stable AMOLED display despite the aging effects in the a-Si:H thin film transistors and OLED, without increasing the driving complexity

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 score0.009

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.006
GPT teacher head0.196
Teacher spread0.190 · 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

Citations4
Published2006
Admission routes1
Has abstractyes

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