Fluorescent and lasing whispering gallery mode microresonators for sensing applications
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".