On the use of photoacoustics to detect red blood cell aggregation
Why this work is in the frame
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Bibliographic record
Abstract
The feasibility of detecting red blood cell (RBC) aggregation with photoacoustics (PAs) was investigated theoretically and experimentally using human and porcine RBCs. The theoretical PA signals and spectra generated from such samples were examined for several hematocrit levels and aggregates sizes. The effect of a finite transducer bandwidth on the received PA signal was also examined. The simulation results suggest that the dominant frequency of the PA signals from non-aggregated RBCs decreases towards clinical frequency ranges as the aggregate size increases. The experimentally measured mean spectral power increased by ~6 dB for the largest aggregate compared to the non-aggregated samples. Such results confirm the theoretical predictions and illustrate the potential of using PA imaging for detecting RBC aggregation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it