Comparison of Generated Parallel Capillary Arrays to Three‐Dimensional Reconstructed Capillary Networks in Modeling Oxygen Transport in Discrete Microvascular Volumes
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Bibliographic record
Abstract
OBJECTIVE: We compare RMN to PCA under several simulated physiological conditions to determine how the use of different vascular geometry affects oxygen transport solutions. METHODS: Three discrete networks were reconstructed from intravital video microscopy of rat skeletal muscle (84 × 168 × 342 μm, 70 × 157 × 268 μm, and 65 × 240 × 571 μm), and hemodynamic measurements were made in individual capillaries. PCAs were created based on statistical measurements from RMNs. Blood flow and O₂ transport models were applied, and the resulting solutions for RMN and PCA models were compared under four conditions (rest, exercise, ischemia, and hypoxia). RESULTS: Predicted tissue PO₂ was consistently lower in all RMN simulations compared to the paired PCA. PO₂ for 3D reconstructions at rest were 28.2 ± 4.8, 28.1 ± 3.5, and 33.0 ± 4.5 mmHg for networks I, II, and III compared to the PCA mean values of 31.2 ± 4.5, 30.6 ± 3.4, and 33.8 ± 4.6 mmHg. Simulated exercise yielded mean tissue PO₂ in the RMN of 10.1 ± 5.4, 12.6 ± 5.7, and 19.7 ± 5.7 mmHg compared to 15.3 ± 7.3, 18.8 ± 5.3, and 21.7 ± 6.0 in PCA. CONCLUSIONS: These findings suggest that volume matched PCA yield different results compared to reconstructed microvascular geometries when applied to O₂ transport modeling; the predominant characteristic of this difference being an over estimate of mean tissue PO₂. Despite this limitation, PCA models remain important for theoretical studies as they produce PO₂ distributions with similar shape and parameter dependence as RMN.
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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) | 0.001 | 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 | 0.000 | 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