A Low-Cost Digital Microscope with Real-Time Fluorescent Imaging Capability
Bibliographic record
Abstract
This paper describes the development of a prototype of a low-cost digital fluorescent microscope built from commercial off-the-shelf (COTS) components. The prototype was tested to detect malignant tumor cells taken from a living organism in a preclinical setting. This experiment was accomplished by using Alexa Fluor 488 conjugate dye attached to the cancer cells. Our prototype utilizes a torch along with an excitation filter as a light source for fluorophore excitation, a dichroic mirror to reflect the excitation and pass the emitted green light from the sample under test and a barrier filter to permit only appropriate wavelength. The system is designed out of a microscope using its optical zooming property and an assembly of exciter filter, dichroic mirror and transmitter filter. The microscope is connected to a computer or laptop through universal serial bus (USB) that allows real-time transmission of captured florescence images; this also offers real-time control of the microscope. The designed system has comparable features of high-end commercial fluorescent microscopes while reducing cost, power, weight and size.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".