Investigation of photoacoustic signal strength as a function of scan-speed and laser-repetition-rate
Bibliographic record
Abstract
Optical-resolution photoacoustic microscopy (OR-PAM) can produce micron-scale, high-resolution images of optically-absorbing chromophores. The pressure rise of photoacoustic signals is proportional to the Grueneisen parameter, which is temperature dependent. High laser repetition-rates may cause overlapping of adjacent laser pulses on targets in laser-scanning OR-PAM. When laser-pulse-repetition intervals are shorter than thermal relaxation times, the zone of laser-spot overlap between pulses can generate higher photoacoustic signal than cases where beam-spots do not overlap or in cases where laser pulse-intervals are longer than the thermal relaxation time. This is because subsequent laser pulses experience higher Grueneisen parameters than previous pulses due to temperature rises induced by the previous pulses. Here, we present our recent studies on photoacoustic signals strength varying with scanning speed and laser-repetition-rate on black tape, human hair and rat blood respectively.
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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 | 0.002 |
| 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".