Synthetic images of blood microcirculation to assess precision of velocity profiles by a cross-correlation method
Bibliographic record
Abstract
Optical cross-correlation methods have been used to study the motion of red blood cells (RBC) in the microcirculation. To evaluate the precision of such a method to determine RBC velocity profiles, we developped a computational model of the microscopy image formation. The following steps were undertaken: (1) a mechanical model was used to mimic three dimensional RBC movements in a tubular parabolic flow; (2) at each time step, a synthetic image was built using microscopic image formation equations based on the depth of correlation of RBCs; and (3) the velocity profile was extracted by a cross-correlation algorithm applied to these synthetic images. The estimated maximum velocities extracted from the simulated images were always smaller than velocities found by simulation. Relative errors (4% to 25%) depended on the vessel radius and on the shape of the velocity profile, but not on the hematocrit or on the maximum velocity.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".