<title>FDTD modelling of the cell membrane and gold nanoparticles effects on optical immersion experiments</title>
Bibliographic record
Abstract
The FDTD modeling technique is applied to provide additional insight on the effect of the cell membrane thickness in optical immersion enhanced phase contrast microscope imaging. Pilot results on the application of the FDTD approach for studying the implementation of the optical immersion technique for the visualization of single and multiple gold nanoparticles in biological cells are also presented. The paper focuses on three different scenarios considering single biological cells containing i) cytoplasm and membrane, ii) cytoplasm, nucleus and membrane, and iii) cytoplasm, nucleus, gold nanoparticle(s) and membrane. To the best knowledge of authors, this is the first research study discussing the cell membrane thickness and single gold nanoparticle effects on the forward scattered light from biological cells. The potential of the FDTD approach and its applicability to new and promising biomedical optics research areas such as the study of optical immersion technique enhanced bio-imaging is demonstrated.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".