Playing the notes of DNA with light: extremely high frequency nanomechanical oscillations
Bibliographic record
Abstract
We use a double nanohole (DNH) optical tweezer with two trapping lasers beating to excite the vibrational modes of single-stranded DNA (ssDNA) fragments in the extremely high frequency range. We find the resonant vibration frequency of a 20 base ssDNA to be 40 GHz. We show that the change in the resonant frequency for different lengths of the DNA strand is in good agreement with one dimensional lattice vibration theory. Thus the DNH tweezer system could distinguish between different lengths of DNA strands with resolution down to a few bases. By varying the base sequence and length, it is possible to adjust the resonance frequency vibration spectrum. The technique shows the potential for use in sequencing applications if we can improve the resolution of the present system to detect changes in resonant frequency for a single base change in a given sequence. The technique is single-molecule and label-free as compared to the existing methods used for DNA characterization like gel electrophoresis.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".