Dipole Field Navigation: Theory and Proof of Concept
Why this work is in the frame
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Bibliographic record
Abstract
To achieve the effective navigation of microscale agents in the vascular network, a high magnetic field strength with high directional magnetic gradients are required. So far, the methods that have been investigated support only one of these specifications but not both. Here, we propose a new method dubbed dipole field navigation (DFN) that provides high field strength to bring magnetic agents at saturation magnetization with gradients exceeding 300 mT/m at any depth within the human body. For DFN, the high field strength is achieved by placing the patient in the tunnel of a clinical MRI scanner, while high gradients are generated by the distortions of the scanner's homogeneous field from larger ferromagnetic cores placed at specific locations outside the patient. The main challenge of DFN lies in the methods that are required to adequately place the cores in the tunnel. Here, a first method is presented to solve the inverse magnetic problem of positioning such a set of cores so that microscale agents could be guided through a desired path in the vascular network. As a first proof of concept, magnetic particles were steered successfully in three consecutive bifurcations in a 3-D in vitro network.
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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 | 0.000 | 0.000 |
| 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 it