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Record W2086020403 · doi:10.1889/1.2785620

52.2: A Low‐Cost Stable Amorphous Silicon AMOLED Display with Full V <sub>T</sub> ‐ and V <sub>OLED</sub> Shift Compensation

2007· article· en· W2086020403 on OpenAlexaff
G. Reza Chaji, Stefan Alexander, Arokia Nathan, Corbin Church, S. J. Tang

Bibliographic record

VenueSID Symposium Digest of Technical Papers · 2007
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsIGNIS Innovation (Canada)
Fundersnot available
KeywordsAMOLEDOLEDMaterials scienceCompensation (psychology)OptoelectronicsPixelElectronic engineeringComputer scienceElectrical engineeringThin-film transistorEngineeringNanotechnologyActive matrixArtificial intelligenceLayer (electronics)

Abstract

fetched live from OpenAlex

Abstract We present a new simple and low cost pixel circuit and driving scheme for the a‐Si AMOLED displays using conventional AMLCD drivers. Measurement results show significant stability and high immunity to temperature and mobility variations which makes the pixel circuit and driving scheme attractive for implementation in different technologies. A 9‐inch a‐Si AMOLED display fabricated based on this driving scheme shows high uniformity and long lifetime.

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 score0.004
Threshold uncertainty score0.014

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.004
GPT teacher head0.186
Teacher spread0.182 · 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

Citations10
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueSID Symposium Digest of Technical PapersSame topicThin-Film Transistor TechnologiesFrench-language works237,207