Mosaic acquisition and processing for optical-resolution photoacoustic microscopy
Bibliographic record
Abstract
In optical-resolution photo-acoustic microscopy (OR-PAM), data acquisition time is limited by both laser pulse repetition rate (PRR) and scanning speed. Optical-scanning offers high speed, but limited, field of view determined by ultrasound transducer sensitivity. In this paper, we propose a hybrid optical and mechanical-scanning OR-PAM system with mosaic data acquisition and processing. The system employs fast-scanning mirrors and a diode-pumped, nanosecond-pulsed, Ytterbium-doped, 532-nm fiber laser with PRR up to 600 kHz. Data from a sequence of image mosaic patches is acquired systematically, at predetermined mechanical scanning locations, with optical scanning. After all imaging locations are covered, a large panoramic scene is generated by stitching the mosaic patches together. Our proposed system is proven to be at least 20 times faster than previous reported OR-PAM systems.
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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 | 0.001 |
| 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) | 0.002 | 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".