The Potential Influence of the Microbiota and Probiotics on Women during Long Spaceflights
Bibliographic record
Abstract
Humans have been exploring space for almost 55 years but space travel comes with many psychological and physiological changes that astronauts have to adapt to, both during and post flight missions. Now, with the reality of such missions lasting years, maintaining proper health of the flight crew is a high priority. While conditions such as nausea, bone loss, renal calculi and depression have been recognized, and approaches to medical and surgical care in space considered, the influence of the microbiota could be of added significance in maintaining astronaut health. While probiotics have long been part of the Russian cosmonaut diet, their use for specific health concerns of women has not been assessed. In this article, we explore the ways in which the microbiome may influence the health of female astronauts during long space flights, and present a rationale for the use of probiotics.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".