Humans on the International Space Station-How Research, Operations, and International Collaboration are Leading to New Understanding of Human Physiology and Performance in Microgravity
Bibliographic record
Abstract
As the International Space Station (ISS) nears completion, and full international utilization is achieved, we are at a scientific crossroads. ISS is the premier location for research aimed at understanding the effects of microgravity on the human body. For applications to future human exploration, it is key for validation, quantification, and mitigation of a wide variety of spaceflight risks to health and human performance. Understanding and mitigating these risks is the focus of NASA s Human Research Program. However, NASA s approach to defining human research objectives is only one of many approaches within the ISS international partnership (including Roscosmos, the European Space Agency, the Canadian Space Agency, and the Japan Aerospace Exploration Agency). Each of these agencies selects and implements their own ISS research, with independent but related objectives for human and life sciences research. Because the science itself is also international and collaborative, investigations that are led by one ISS partner also often include cooperative scientists from around the world. The operation of the ISS generates significant additional data that is not directly linked to specific investigations. Such data comes from medical monitoring of crew members, life support and radiation monitoring, and from the systems that have been implemented to protect the health of the crew (such as exercise hardware). We provide examples of these international synergies in human research on ISS and highlight key early accomplishments that derive from these broad interfaces. Taken as a whole, the combination of diverse research objectives, operational data, international sharing of research resources on ISS, and scientific collaboration provide a robust research approach and capability that no one partner could achieve alone.
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.
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 | 0.001 |
| 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".