Are We Learning as Much as Possible from Spaceflight to Better Understand Health and Risks to Health on Earth, as Well as in Space?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The objective of this review is to discuss the changes in human biology and physiology that occur when humans, who evolved on Earth for millions of years, now are subjected to space flight for extended periods of time, and how detailing such changes associated with space flight could help better understand risks for loss of health on Earth. Space programs invest heavily in the selection and training of astronauts. They also are investing in maintaining the health of astronauts, both for extensive stays in low earth orbit on ISS, and in preparation for deep space missions in the future. This effort is critical for the success of such missions as the N is small and the tasks needed to be performed in a hostile environment are complex and demanding. However, space is a unique environment, devoid of many of the “boundary conditions” that shaped human evolution (e.g. 1 g environment, magnetic fields, background radiation, oxygen, water, etc). Therefore, for humans to be successful in space, we need to learn to adapt and minimize the impact of an altered environment on human health. Conversely, we can also learn considerably from this altered environment for life on earth. The question is, are we getting the maximal information from life in space to learn about like on earth? The answer is likely No, and as such, our “Return on Investment” is not as great as it could be. Even though the number of astronauts is not large, what we can learn from them could help shape new questions for research focused on health for those on earth, as well is contribute to “precision health” from the study of astronaut diversity. This latter effort would contribute to both the health of astronauts identifying risks, as well as contribute to health on earth via better understanding of the human genome and epigenome, as well as factors contributing to risk for diseases on earth, particularly as individuals age and regulatory systems become altered. Better use of the International Space Station, and similar platforms in the future, could provide critical insights in aging-associated risks for loss of health on Earth, as well as promote new approaches to using precision medicine to overcome threats to health while in space. To achieve this goal will likely require advanced approaches to collecting such information and use of more systems biology, systems physiology approaches to integrate the information.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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