The development of Magnetic Resonance Imaging (MRI) technology for use in space—A progress report
Bibliographic record
Abstract
We have been developing Magnetic Resonance Imaging (MRI) technology that is suitable for imaging astronauts in space for a little more than a decade. The technology may be classified as “gradient-free” MRI and works by using Radio Frequency (RF) spatial phase encoding instead of the usual magnetic field gradient mediated spatial frequency encoding. Here a progress report is given along with an outline of where and how MRI can be used in future space flight. To date we have completed several design concept studies for the Canadian Space Agency (CSA), have flown a prototype in zero-g and have developed an approach that can realize the CSA’s Health Beyond vision for the MRI technology. The first applications for MRI in space will be for research on the effects of space flight on the human body, especially that of interplanetary radiation. Following that, MRI can be a central part of an integrated spacecraft medical system and used for diagnostic medical purposes.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".