Mimicking Multimodal Contrast with Vertex Component Analysis of Hyperspectral CARS Images
Why this work is in the frame
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Bibliographic record
Abstract
We show the applicability of vertex component analysis (VCA) of hyperspectral CARS images in generating a similar contrast profile to that obtained in “multimodal imaging” that uses signals from three separate nonlinear optical techniques. Using an atherosclerotic rabbit aorta test image, we show that the VCA algorithm provides pseudocolor contrast that is comparable to multimodal imaging, thus suggesting that under certain conditions much of the information gleaned from a multimodal nonlinear optical approach can be sufficiently extracted from the CARS hyperspectral stack itself. This is useful for unsupervised contrast generation on hyperspectral CARS implementations such as multiplex CARS that may not have multimodal capabilities. The utility of VCA as a quantitative analysis tool in CARS is also addressed.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.000 |
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