Improving photoacoustic imaging of lymphatic dynamics in pigmented mice
Bibliographic record
Abstract
Recent advances in optical imaging and spectroscopy of biological tissues facilitated groundbreaking discoveries in physiology of the lymphatic system of mammals. One important aspect is the dynamics of the lymphatic drainage between the eyes and the brain, which was potentially linked to a number of diseases. A mouse is a versatile model providing convenient in-vivo and ex-vivo studies of lymphatic drainage by multispectral optoacoustic tomography (MSOT) using near-infrared exogenous tracers. The accuracy of the in-vivo spectral umixing of chromohores by MSOT still requires further improvement to achieve required resolution. To achieve this goal, we studied factors such as the spectrum of wavelengths and skin pigmentation affecting the quantitative accuracy of MSOT tracking of the novel hybrid photoacoustic-fluorescent contrast agent QC-1/BSA/BODIPY injected into the lymph of C57 pigmented mice. We also compared performances of various spectral algorithms.
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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".