Bibliographic record
Abstract
Summary form only given. It is well known that the eigen frequency (f) of a harmonic oscillator is determined by the oscillator effective mass (meff) and spring constant (keff) according to the Hook's law f = 1/2π √(keff/mejj). An optical whispering gallery microcavity, when the wavelength of the injected light coincides the cavity resonance, establishes tremendous amount of light circulating along its equator. For an ultra-high quality factor microcavity, the circulating light exerts an optical force strong enough to turn the cavity to an opto-mechanical oscillator with an injected light power as low as several milliwatts in an aqueous environment. Following the Hook's law, a small particle binding on the surface of the cavity increases the effective mass, thus changes the corresponding frequency of the oscillator. Researchers have shown that this change of the frequency can be interrogated by monitoring the light escaping from the cavity. This makes the cavity a particle detector with pico-gram resolution. Here, we show that due to the forced oscillator nature of a silica microsphere, the binding particle also alters the rigidity or spring constant of the cavity through the tuning of the optical force. Such effect produces a shift of the oscillation frequency orders of magnitude larger than that induced from the addition of the particle mass. Using this principle, single 10-nm-raidus silica beads was detected and Bovine serum albumin (BSA) molecule with molecular weight of 66 kDalton was also observed at a high signal-to-noise ratio (SNR) of 16.8. The experiment predicts a minimum detection sensitivity of 3.9 kDalton with an SNR above unity. As the resolution of this technique is limited by optical and effective mechanical quality factor, further improvement predicts a sub-atomic resolution.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.068 | 0.013 |
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".