Accelerated Detection of Viral Particles by Combining AC Electric Field Effects and Micro-Raman Spectroscopy
Bibliographic record
Abstract
A detection method that combines electric field-assisted virus capture on antibody-decorated surfaces with the "fingerprinting" capabilities of micro-Raman spectroscopy is demonstrated for the case of M13 virus in water. The proof-of-principle surface mapping of model bioparticles (protein coated polystyrene spheres) captured by an AC electric field between planar microelectrodes is presented with a methodology for analyzing the resulting spectra by comparing relative peak intensities. The same principle is applied to dielectrophoretically captured M13 phage particles whose presence is indirectly confirmed with micro-Raman spectroscopy using NeutrAvidin-Cy3 as a labeling molecule. It is concluded that the combination of electrokinetically driven virus sampling and micro-Raman based signal transduction provides a promising approach for time-efficient and in situ detection of viruses.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".