Evaluating the Suitability of Perfusion-Based PD Probes for Use in Altered Gravity Environments
Bibliographic record
Abstract
Measurable changes in electrophysiology have been documented in spaceflight, creating a pathway for disease genesis and progression in astronauts. These electrophysiology changes can be measured using potential difference (PD). A probe to measure PD was developed and is used clinically on Earth; this probe relies on fluid perfusion to establish an electrical connection to make PD measurements. The changes to fluid behavior in microgravity and partial gravity (including lunar and Martian gravity) drives the need to test this probe in a spaceflight environment. Here, we test the PD probe in a novel nasal cavity phantom in parabolic flight, simulating microgravity, lunar gravity, Martian gravity, and hypergravity conditions across 37 parabolas. The results are evaluated across gravity conditions using the Wilcoxon Rank Sum test. We record no statistically significant difference in probe PD measurements in 1 g, microgravity, lunar gravity, and hypergravity (approximately 1.8 g) conditions, reaching a NASA Technology Readiness Level 6. Martian gravity findings are inconclusive. Perfusion-based PD probes are therefore successfully demonstrated for use in spaceflight operation in microgravity, lunar gravity, and hypergravity environments; this establishes a foundation for moving towards the in-space testing of perfusion-based probes in astronauts.
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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 | 0.002 |
| 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 | 0.001 |
| 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".