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Record W1498724494 · doi:10.1002/9781119506003.ch9

Properties and Applications of Photonic Crystals

2019· other· en· W1498724494 on OpenAlexaff
Harry E. Ruda, Naomi Matsuura

Bibliographic record

Venuenot available
Typeother
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhotonic crystalPhotonicsMiniaturizationNanotechnologyPhotonic metamaterialVariety (cybernetics)OptoelectronicsMaterials scienceComputer science

Abstract

fetched live from OpenAlex

Photonic crystals offer a well-recognized ability to control the propagation of modes of light in an analogous fashion to how nanostructures have been harnessed to control electron-based phenomena. This has led to proposals – and indeed demonstrations – of a wide variety of photonic-crystal-based photonic devices with applications in areas including communications, computing, and sensing, for example. In such applications, photonic crystals can offer both a unique performance advantage as well as potential for substantial miniaturization of photonic systems. This chapter outlines the practical aspects of implementing photonic crystal structures, together with their associated properties for a range of applications, stressing both passive and active or tunable structures. The future for such artificially engineered structures appears bright with strong prospects in areas as diverse as sensing, telecommunications, medicine, and consumer products, to name a few.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.472
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

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)0.0040.000

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 head0.013
GPT teacher head0.229
Teacher spread0.217 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations4
Published2019
Admission routes1
Has abstractyes

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