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Record W2989871442 · doi:10.1002/jsid.858

Model for assessing organic light‐emitting diode display lifetime across applications

2019· article· en· W2989871442 on OpenAlex
Michael E. Miller, Jérémie Gerhardt, Hyunjin Yoo, Tara Akhavan

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

VenueJournal of the Society for Information Display · 2019
Typearticle
Languageen
FieldEngineering
TopicGreen IT and Sustainability
Canadian institutionsOralys (Canada)
Fundersnot available
KeywordsOLEDLuminanceDiodeComputer scienceOptoelectronicsDisplay devicePower consumptionPower (physics)Materials sciencePhysicsComputer vision

Abstract

fetched live from OpenAlex

Abstract A model for assessing organic light‐emitting diode (OLED) display lifetime is developed and discussed for estimating OLED display lifetime in various applications. The lifetime model extends existing stretched exponential models of luminance decay for OLED devices to permit this decay to be estimated as a function of time and current density. This extended model is illustrated within an application to assess the power consumption and luminance decay of diodes within an OLED display. Various metrics of display lifetime are discussed with the aim of developing methods to assess the perceived lifetime of an OLED display to global and local luminance decay mechanisms. Finally, these metrics are applied to illustrate the performance of the model for assessing the impact of an image processing algorithm on OLED display 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.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.608
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.252
Teacher spread0.245 · 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