Plasmonic Biosensors on a Chip for Point-of-Care Applications
Bibliographic record
Abstract
Plasmonic biosensors have emerged as one of the most suitable sensors for future cost-effective clinical analysis and point-of-care platforms. They are based on the plasmonic properties of gold nanoparticles and nanostructures, principally, on the sensitivity of the gold plasmon band to any change in the surrounding environment. The successful development of plasmonic biosensors are the result of the progress in nanotechnology and microfabrication and the next step, their integration in a lab-on-a-chip, allows their miniaturization and portability. Miniaturized devices will find their way to clinics and patient's bedside as well as to remote places and developing countries, improving healthcare for everybody. In this paper, in the beginning, a short introduction on the phenomenon of plasmonics, the basic configurations of the instruments, and approaches for sensing are provided. Then, the advantages stemming from the integration of plasmonic biosensors into a microfluidic device are emphasized. The end product of a successful integration and miniaturization process is a high-performance, point-of-care device with benefits to healthcare and personalized medicine.
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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) | 0.000 | 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 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".