Fabrication and validation of an LED array microscope for multimodal, quantitative imaging
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
The combination of multiple imaging modalities in a single microscopy system can enable new insights into biological processes. In this work, we describe the construction and rigorous characterization of a custom microscope with multimodal imaging in a single, cost-effective system. Our design utilizes advances in LED technology, robotics, and open-source software, along with existing optical components and precision optomechanical parts to offer a modular and versatile design. This microscope is operated using software written in Arduino and Python and has the ability to run multi-day automated imaging experiments when placed inside of a cell culture incubator. Additionally, we provide and demonstrate methods to validate images taken in brightfield and darkfield, along with validation and optimization for differential phase contrast (DPC) quantitative phase imaging.
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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 | 0.000 | 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) | 0.000 | 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