Tri-modal microscopy with multiphoton and optical coherence microscopy/tomography for multi-scale and multi-contrast imaging
Why this work is in the frame
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Bibliographic record
Abstract
Multi-scale multimodal microscopy is a very useful technique by providing multiple imaging contrasts with adjustable field of views and spatial resolutions. Here, we present a tri-modal microscope combining multiphoton microscopy (MPM), optical coherence microscopy (OCM) and optical coherence tomography (OCT) for subsurface visualization of biological tissues. The advantages of the tri-modal system are demonstrated on various biological samples. It enables the visualization of multiple intrinsic contrasts including scattering, two-photon excitation fluorescence (TPEF), and second harmonic generation (SHG). It also enables a rapid scanning over a large tissue area and a high resolution zoom-in for cellular-level structures on regions of interest. The tri-modal microscope can be important for label-free imaging to obtain a sufficient set of parameters for reliable sample analysis.
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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 | 0.001 |
| 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