Macroscopic fluorescent lifetime imaging in turbid media using angular filter arrays
Bibliographic record
Abstract
We describe an optical imaging methodology applicable to the detection of a fluorescent agent below the surface of turbid media with lifetime property extraction. The method exploits the collimation detection capabilities of an angular filter array to form a projection image of a fluorophore embedded within the tissue-mimicking phantom. A femto-second pulsed laser was used to illuminate the tissue and excite the fluorophore within the medium. Fluorescent emission passing through the angular filter array was detected by an ultra fast gate intensified CCD camera. The array accepted photons with trajectories within 0.5 degree of the axis of each micro-tunnel and rejected most of the scattered fluorescent light exiting the tissue. The performance of the angular filter array did not depend on coherence or wavelength of the laser illumination. It was observed that resulted images had sub-millimeter resolution within 5 mm deep into the turbid media and can have a large field of view (approximately 2 cm x 2 cm).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".