On the potential application of surface plasmon-based core-shell particles to study blood functional parameters
Bibliographic record
Abstract
Abstract We investigated the application of gold nanoshell particles as optical sensors and contrast agents to study the blood functional parameters. Gold nanoshell particles with a core size of 1 μ m that exhibit two prominent plasmonic peaks at 750 and 830 nm were developed. The peaks correspond to the wavelengths typically used to study the oxygen saturation of the blood. The plasmonic properties of gold nanoshells in media with various refractive indices were studied. Glucose samples with concentrations 0, 15, and 20%w/v in water were used. The 750 and 830 nm plasmonic peaks exhibit peak wavelength shifts of 63.77 ± 49.40 nm and 31.18 ± 20.94 nm per unit refractive index change. The optical properties of blood samples mixed with gold nanoshells were also measured. The optical absorption of blood samples increased by 7% at these wavelengths in the presence of the nanoshells. The plasmonic peaks at 750 and 830 nm showed a 3.57 ± 0.56 and 1.44 ± 0.55 percentage variation in absorbance for a 1% change in hematocrit. The enhanced optical absorption at these wavelengths suggests that these particles are effective optical sensors/contrast agents for multimodal optical and photoacoustic sensing and imaging.
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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) | 0.000 | 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".