Estimating blood flow in skeletal muscle arteriolar trees reconstructed from in vivo data using the Fry approach
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To develop a computational method to accurately predict blood flow in skeletal muscle arteriolar trees in the absence of complete boundary data. METHODS: We used arteriolar trees in the rat GM muscle that were reconstructed from montages obtained via IVVM, and incorporated a recently published method for approximating unknown b.c.'s into our existing two-phase, steady-state blood flow model. For varying numbers of unknown b.c.'s, we used the new flow model and GM geometry to approximately match RBC flows corresponding to experimental measurements. RESULTS: We showed this method gives errors that decrease as the number of unknown b.c.'s decreases. We also showed that specifying total blood flow decreases the mean RBC flow error and its variability. By varying required target values of intravascular pressure and wall shear stress, we showed results are less sensitive to target pressure. Finally, we developed and validated a method for determining target values, so that network hemodynamics and resistance can be accurately calculated based only on measured or estimated total blood flow. CONCLUSIONS: We have developed and validated a computational method that can accurately estimate RBC flow distribution in skeletal muscle arteriolar trees in the absence of complete boundary data.
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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