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Record W3176190267 · doi:10.1002/sdtp.14714

34‐1: Evaluating and Minimizing Color Distortion in Wide‐Gamut Displays Due to Variations of Cone Fundamentals among Color‐Normal Observers

2021· article· en· W3176190267 on OpenAlexaff
Lorne Whitehead, Kevin Smet

Bibliographic record

VenueSID Symposium Digest of Technical Papers · 2021
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGamutNarrowbandObserver (physics)Computer scienceComputer visionArtificial intelligencePrimary colorColor differenceCone (formal languages)RGB color modelMathematicsPhysicsTelecommunicationsAlgorithmFilter (signal processing)

Abstract

fetched live from OpenAlex

Narrowband three‐primary displays cause observer‐based metameric failure, whereby normal variations in color vision cause individuals to perceive display colors differently. This problem is reduced with broadband primaries, but so is color gamut. Another solution is to use six narrowband primaries, but this is considered impractical. Color error arises from the diversity of cone fundamentals among color‐normal observers. We recently developed a better way to assess this problem and reduce it. This enables both color accuracy and increased gamut, by optimizing the wavelengths in a four narrowband primary system that is compatible with current hardware and video signals.

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)0.000
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 score0.197
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.045
GPT teacher head0.322
Teacher spread0.277 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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