On-Chip Polarization Light Microscopy
Bibliographic record
Abstract
Polarization light microscopy (PLM) enables detailed examination of birefringent materials and reveals unique features that cannot be observed under non-polarized light. Implementation of this technique for quantitative PLM (QPLM) assessment of samples is challenging and requires specialized components and equipment. Here, we demonstrate QPLM on a semiconductor imaging chip that is suitable for point-of-care/need applications. A white LED illumination was used with crossed polarizers and a full wave plate to perform on-chip, non-contact-mode QPLM. Polarization complexity is probed by assessing the multispectral phase shift experienced by white light through the distinct optical paths of the sample. This platform can achieve micrometer-scale spatial resolution with a Field of View determined by the size of the semiconductor sensor. Visualization of a biological sample (Euglena gracilis) was demonstrated, as well as the detection of Monosodium Urate crystals, where the presence of negative birefringence of crystals in synovial fluid is important for the diagnosis of gout.
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How this classification was reachedexpand
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) | 0.001 | 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 teacher head, 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".