Monitoring Blood Clot Formation and Lysis in Vitro Using High Frequency Photoacoustics
Bibliographic record
Abstract
Clotting is a survival mechanism that prevents blood loss after injury. An imbalance in clotting factors can lead to lethal consequences such as exsanguination or inappropriate clotting. Existing methods to monitor clot formation and lysis measure viscoelasticity of whole blood or optical density of plasma over time. Though these methods provide insights into coagulation and fibrinolysis, they require 1-3 millilitres of blood which can worsen anemia especially in small pediatric patients or provide partial information as seen with acellular plasma-based measurements. To overcome these limitations, a high frequency (HF) photoacoustic (PA) imaging was developed to detect clot formation and lysis in whole blood. Frequency spectra showed continuous changes in unclotted blood which became more stable during clotting. After clot lysis, the frequency spectra changed continuously as seen with whole blood. HFPA imaging can differentiate clotting and lysis with small volumes of blood (25µL/test).
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".