Benefit of Repeated Receptor Stimulation as a Spaceflight Medical Tool to Promote Cardiovascular Fitness: Different Orthostatic Paradigms Compared
Bibliographic record
Abstract
We used various orthostatic stimulus combinations to better understand the physiology and countermeasure potential of repeated change of body position in humans. The purpose of the investigations reported was threefold: To investigate cardiovascular and hormonal effects of repeated transition between partially antiorthostatic (-30 degrees HDT) and partially head-up passive body tilt (+30 degrees HUT). Protocol Y denotes the repeated transition between these two body positions; To apply, in the same test persons, repeated transition between supine and passive upright (Protocol X), and to compare the effect of the two protocols; To find out which stimulus pattern provides the largest physiological effects and, hence, presumably the largest countermeasure potential. We chose our tilt protocol according to tilt angle sine ranges: The sine difference is 1.0 both in Protocol X (sine=0 vs. sine=1.0) and Y (sine= -0.5 vs. sine= +0.5) since this difference, and not the angle change per se, determines hydrostatic effect intensities. Due to longer-lasting neurohormonal effects elicited by tilting procedures, they all should be a useful countermeasure against post-immobilization orthostatic instability, a conjecture not yet been tested in this specific form. Therefore, one of the questions asked in this study were if movement between the two defined body positions produces similar changes when employing Protocol X vs. Protocol Y.
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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 | 0.000 | 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) | 0.001 | 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".