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Record W2597387991 · doi:10.1002/lpor.201600265

Fluorescent and lasing whispering gallery mode microresonators for sensing applications

2017· article· en· W2597387991 on OpenAlex

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

VenueLaser & Photonics Review · 2017
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Alberta
FundersAustralian Research CouncilARC Centre for Nanoscale BioPhotonics
KeywordsWhispering-gallery waveLasing thresholdResonatorLimitingFluorescenceOptoelectronicsMaterials scienceWhispering galleryOpticsLaserPhysicsEngineering

Abstract

fetched live from OpenAlex

Abstract Whispering gallery modes (WGMs) have been exploited for a broad range of sensing applications. However, the vast majority of WGM sensors consist of passive resonators, requiring complex interrogation systems to be employed, ultimately limiting their practicality. Active resonators containing a gain medium, allowing remote excitation and collection of the WGM‐modulated fluorescence spectra, have emerged as an alternative to passive resonators. Although research is still in its infancy, recent progress has reduced the performance gap between the two paradigms, fueled by the potential for new applications that could not previously be realized. Here, recent developments in sensors based on active WGM microresonators are reviewed, beginning with a discussion of the theory of fluorescence‐based and lasing WGMs, followed by a discussion of the variety of gain media, resonator architectures, and emerging sensing applications. We conclude with a discussion of the prospects and future directions for improving active WGM sensors. image

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.842
Threshold uncertainty score0.740

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)0.0000.000

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 head0.015
GPT teacher head0.277
Teacher spread0.262 · 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