A Method for Detecting Chaos in Canine Myocardial Microcirculatory Red Cell Flux
Bibliographic record
Abstract
Objective: To determine whether red cell movement, as measured by laser Doppler velocimetry, in the capillary net of the beating heart is chaotic. Methods: Using two dog hearts, in situ red blood cell flux was measured at many sites. Simultaneously, epicardial arterial flow and left ventricular pressure were recorded via transit-time flowmeter and catheter manometer, respectively. The presence or absence of chaos was tested by two methods: Lyapunov exponents and correlation dimension. Results: For capillary red cell flux, the Lyapunov was strongly positive at most sites. It was less so for coronary arterial flow and least for left ventricular pressure. Correlation dimension calculation was less able to distinguish the presence or absence of chaos in capillary red cell tissue flux, coronary arterial flow, and left ventricular pressure. Conclusions: Capillary red cell flux (movement of red cells in capillaries) is nonlinear, (i.e., chaotic). This complexity suggests that the primary control for oxygen delivery to cardiac myocytes by red blood cells resides in the microcirculation. Also, capillary red cell flux is bifractal, suggesting an ordering of control.
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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 | 0.002 | 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) | 0.001 | 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".