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Record W3190690545 · doi:10.1039/d1sc03447b

Shedding light on predicting and controlling emission chromaticity in multicomponent photoluminescent systems

2021· article· en· W3190690545 on OpenAlexafffund
Jayden Price, Barbora Balónová, Barry A. Blight, Sara Eisler

Bibliographic record

VenueChemical Science · 2021
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence and Fluorescent Materials
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaNew Brunswick Innovation Foundation
KeywordsChromaticityPhotoluminescenceOptoelectronicsMaterials scienceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

M), colour tuning within these systems was controlled by (1) varying the composition of the components and (2) exploiting the differences in the components' excitation intensities at common wavelengths. Using this approach, white light emission (WLE) was realized using a pre-determined mixture of red, green, and blue emitting organic molecules. Based on these results, materials and devices with built-in or programmable emission colour can be achieved, including highly sought-after WLE.

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 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)0.001
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 score0.016
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.011
GPT teacher head0.249
Teacher spread0.238 · 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 teacher head, 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

Citations11
Published2021
Admission routes2
Has abstractyes

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