Three-Color Fluorescence Cross-Correlation Spectroscopy for Analyzing Complex Nanoparticle Mixtures
Bibliographic record
Abstract
Further insight toward the complex association and dissociation events of macromolecules requires the development of a spectroscopic technique that can track individual components, or building blocks of these macromolecules, and the complexes which they form, in real time. Three-color fluorescence cross-correlation spectroscopy (3C-FCCS) has been shown to track assemblies of three spectrally labeled species in solution. Here, we clearly show that 3C-FCCS is capable of distinguishing beads barcoded with quantum dots from free quantum dots in the background despite the 800-to-1 difference in concentration of these two components. The validation of this spectroscopic technique in combination with the development of barcode labels would enable one to start to investigate complex association and dissociation kinetics of macromolecules and nanomaterials during the assembly process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 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 teacher head, 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".