Development of an ESR/MR Dual-imaging System as a Tool to Detect Bioradicals
Bibliographic record
Abstract
A system combining electron spin resonance imaging (ESRI) with another imaging modality capable of enabling visualization of the distribution of bioradicals on an anatomical map of the specimens would be a superior biomedical imaging system. We describe the development of an ESR/MR dual-imaging system with one permanent magnet and the biomedical applications of this system. The magnetic circuit developed for the ESR/MR dual-imaging system consisted of the permanent magnet made of Fe-Nd-B, pole pieces, and poke. The permanent magnet was installed on the MR side only, and the ESR side was made of pole pieces only. The magnetic field was adjusted to 0.5T at MR and to 0.042T at ESR. The overall dimensions of the magnet developed for the ESR/MR imaging system were 460 (W)x440 (D)x460 (H) mm, and it weighed 220 kg. The distance of each center for the magnet for ESR and MR imaging could be set as close as 200 mm. The entire ESR/MR imaging system can be installed in a common laboratory without magnetic shielding. MR images of plants (myoga) and small animals (mice and rats) were successfully acquired with or without ESR operation. ESR spectra of nitroxyl spin probes were also measured, even with MRI operation. ESR signals of triarylmethyl derivatives with narrow line-width (0.026 mT) were observed in living mice while MRI was operating. The ESR/MR imaging dual functions work properly with no electric or magnetic interference. The ESR/MR dual images demonstrate that this system enables visualization of the distribution of bioradicals on the anatomical map of the object.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".