Development of a fast-scanning combined ultrasound-photoacoustic biomicroscope
Bibliographic record
Abstract
Recently a realtime photoacoustic microscopy system has been demonstrated. Unfortunately, however, displayed B-scan images were sometimes difficult to interpret as there was little structural context. In this work, we provide structural context for photoacoustic microscopy images by adding ultrasound biomicroscopy as a complementary and synergistic modality. Our system uses a voice-coil translation stage capable of 1" lateral translation, and can operate in excess of 15 Hz for 1-cm translations, providing up to 30 ultrasound frames per second. The frame-rate of the photoacoustic acquisitions is limited by the 20-Hz pulse-repetition rate of the laser, but can be increased with a faster-repetition-rate laser. Data from the system is streamed in real time from a 2GS/s PCI data acquisition card to the host PC at rates as high as 200 MB/s. The system should prove useful for various in vivo studies, including combined ultrasound Doppler and photoacoustic imaging.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".