Design and analysis of a spectro-angular surface plasmon resonance biosensor operating in the visible spectrum
Bibliographic record
Abstract
Surface plasmon resonance (SPR) sensing is one of the most widely used methods to implement biosensing due to its sensitivity and capacity for label-free detection. Whilst most commercial SPR sensors operate in the angular regime, it has recently been shown that an increase in sensitivity and a greater robustness against noise can be achieved by measuring the reflectivity when varying both the angle and wavelength simultaneously, in a so-called spectro-angular SPR biosensor. A single value decomposition method is used to project the two-dimensional spectro-angular reflection signal onto a basis set and allow the image obtained from an unknown refractive index sample to be compared very accurately with a pre-calculated reference set. Herein we demonstrate that a previously reported system operated in the near infra-red has a lower detection limit when operating in the visible spectrum due to the improved spatial resolution and numerical precision of the image sensor. The SPR biosensor presented here has an experimental detection limit of 9.8 × 10(-7) refractive index unit. To validate the system as a biosensor, we also performed the detection of synthetic RNA from pathogenic Legionella pneumophila with the developed biosensing platform.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".