Optical Hyperpolarization of Noble Gases for Medical Imaging
Bibliographic record
Abstract
Magnetic resonance imaging (MRI) of human or animal lungs became possible with the application of hyperpolarized noble gases, such as 3He or 129Xe. This method allows obtaining information on lung morphology and functionality. Introduction of hyperpolarized noble gases provided as well a new tool for non-medical applications such as neutron filters or nuclear magnetic resonance (NMR) spectroscopy studies in porous materials. The high polarization of noble gases is possible using so-called optical pumping methods. In this chapter the two most common polarization techniques of noble gases (3He and 129Xe), spin exchange optical pumping (SEOP) and metastability exchange optical pumping (MEOP) are presented. Variations of these methods delivering higher 3He and 129Xe polarization including hybrid SEOP or MEOP in standard conditions and in elevated pressure and high magnetic fields are also reported. A short description of the equipment used for gas polarization is also provided.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.012 |
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".