Macroscopic optical imaging technique for wide-field estimation of fluorescence depth in optically turbid media for application in brain tumor surgical guidance
Why this work is in the frame
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Bibliographic record
Abstract
A diffuse imaging method is presented that enables wide-field estimation of the depth of fluorescent molecular markers in turbid media by quantifying the deformation of the detected fluorescence spectra due to the wavelength-dependent light attenuation by overlying tissue. This is achieved by measuring the ratio of the fluorescence at two wavelengths in combination with normalization techniques based on diffuse reflectance measurements to evaluate tissue attenuation variations for different depths. It is demonstrated that fluorescence topography can be achieved up to a 5 mm depth using a near-infrared dye with millimeter depth accuracy in turbid media having optical properties representative of normal brain tissue. Wide-field depth estimates are made using optical technology integrated onto a commercial surgical microscope, making this approach feasible for real-world applications.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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