Metal clad waveguide (MCWG) based imaging using a high numerical aperture microscope objective
Bibliographic record
Abstract
Evanescent-field based methods such as surface plasmon resonance (SPR) have been used very effectively for label-free imaging of microscopic biological material in close proximity to a sensing surface. However, the shallow probing depth of SPR (typically less than ~200 nm) can be problematic when imaging relatively thick biological objects such as cells or bacteria. In this paper, we demonstrate how metal-clad waveguides (MCWG) can be used to achieve deeper probing depth compared to SPR while maintaining good imaging spatial resolution. Comparative numerical simulations of imaging spatial resolution versus probing depth are shown for a number of common SPR, long-range SPR, and MCWG configurations, demonstrating that MCWG offer the best compromise between resolution and depth for imaging thick biological objects. Experimental results of synthetic target and live cell imaging are shown that validate the numerical simulations and demonstrate the capabilities of the method.
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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) | 0.001 | 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".