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Record W2169295554 · doi:10.1002/adfm.200700174

Organic Light Emitting Field Effect Transistors: Advances and Perspectives

2007· article· en· W2169295554 on OpenAlexafffund
Fabio Cicoira, Clara Santato

Bibliographic record

VenueAdvanced Functional Materials · 2007
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsInstitut National de la Recherche Scientifique
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesCanadian Bureau for International Education
KeywordsMaterials scienceElectroluminescenceTransistorOrganic semiconductorOptoelectronicsLight emissionPlanarField-effect transistorSemiconductorActive matrixNanotechnologyThin-film transistorVoltageComputer scienceElectrical engineering

Abstract

fetched live from OpenAlex

Abstract Light emitting field effect transistors based on molecular and polymeric organic semiconductors are multifunctional devices that integrate light emission with the current modulating function of a transistor. The planar geometry of organic light emitting field effect transistors (OLEFETs) offers direct access to the light emission region, providing a unique experimental configuration to investigate fundamental optical and electronic properties in organic semiconductors. OLEFETs show great potential for technological applications such as active matrix full color electroluminescent displays. In this Feature Article we review advances in OLEFETs since their first demonstration in 2003 and we highlight exciting challenges associated with their future development.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

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 communication0.0010.002
Open science0.0000.000
Research integrity0.0010.001
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 head0.003
GPT teacher head0.191
Teacher spread0.187 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations334
Published2007
Admission routes2
Has abstractyes

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