Optimisation of a Holographic Microscope for Microbial Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract

 
 
 
 Background: Tracking of microbial organisms over a volume requires images at multiple focal planes along the orthogonal direction. With most conventional microscopes, this requires repeated readjustments; using Digital Holographic Microscopy (DHM), it is possible to use a set of interference patterns to reconstruct at various distances, thereby creating a 3D stack based off a single image.
 Methods: We used an off-axis Mach-Zehnder DHM for imaging and tracking bacterial movement. We describe the algorithm employed for tracking, as well as our improvement of trackability by testing differences in image contrast with the use of Quantum Dots.
 Results: We show that the use of Quantum Dots resulted in an increase in contrast of approximately 11%.
 Conclusion: We suggest this as a method of increasing resolvability of individual microbes. With a more compact design, the microscope will be applicable in various fields, and can be used remotely for studies of microbial organisms.
 
 
 
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it