Bibliographic record
Abstract
UNLABELLED: Commercial space travel may soon be a reality. If so, microgravity, high acceleration, and radiation exposure, all known hazards, will be accessible to the general public. Therefore, space tourism has medical implications. Even though the first flights will feature space exposure times of only a few minutes, the potential may someday exist for exposure times long enough to warrant careful consideration of the potential hazards to the space-faring public. The effects of acceleration and microgravity exposure are well known on the corps of astronauts and cosmonauts. The effects of space radiation are partially known on astronauts, but much remains to be discovered. However, there are problems using astronaut data to make inferences about the general public. Astronauts are not necessarily representative of the general public, since they are highly fit, highly screened individuals. Astronaut data can tell us very little about the potential hazards of microgravity in pediatric, obstetric and geriatric populations, all of whom are potential space tourists. Key issues in standard setting will be determining acceptable limits of pre-existing disease and inferring medical standards from mission profiles. It will not be a trivial task drafting minimal medical standards for commercial space travel. It will require the collaboration of space medicine physicians, making the best guesses possible, based on limited amounts of data, with limited applicability. A helpful departure point may be the USAF Class 3 medical standard, applicable to NASA payload specialists. It is time to begin preliminary discussions toward defining those standards. KEYWORDS: acceleration, aerospace medicine, medical standards, microgravity, radiation, space, space tourism, environmental hazards, environmental medicine.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.046 | 0.005 |
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".