Interferometry and Fluorescence Detection for Simultaneous Analysis of Labeled and Unlabeled Nanoparticles in Solution
Bibliographic record
Abstract
A novel fluctuation spectroscopy technique based on interferometry is described. The technique, termed scattering interference correlation spectroscopy (SICS), autocorrelates the signals from the forward-scattered and transmitted laser light from nanoparticles (NPs) in solution. SICS has two important features: First, for unlabeled NPs with known refractive index, it analyzes not only the diffusion coefficient but also the effective cross section and concentration in a single measurement. Second, it can be combined with fluorescence correlation spectroscopy (FCS) for simultaneous analysis of labeled and unlabeled NPs. SICS is here demonstrated on unlabeled M13 phages and on unlabeled NPs with diameters of 210 nm down to 26 nm. It is also shown how the combination of SICS and FCS can be used to determine the fraction of fluorescent NPs in a mixture and estimate K(d) from a single binding measurement.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".