Exploiting the responses of magnetotactic bacteria robotic agents to enhance displacement control and swarm formation for drug delivery platforms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Magnetotactic bacteria MC-1 (MTB) synthesize a chain of magnetic nanoparticles called magnetosomes to navigate in deep-sea environments by orienting themselves in the direction of the Earth’s magnetic field. MTB’s inherent mobility and ability to be controlled by exposition to an external magnetic field has become of increasing interest for micromanipulation and drug transport applications. In the traditional control schemes, MTB were oriented by exposure to an external magnetic field causing them to align with the magnetic field lines. Directional changes were applied below a critical frequency and, as such, MTB were still able to swim along the generated magnetic field lines. The approach presented here proposes to apply to the MTB an oscillating magnetic field with a frequency beyond a critical limit to in order to exploit the time averaging magnetic field motion behavior of the bacteria cells. Results indicate that a time-multiplexed magnetic field made of various directional cycling fields can control the MTB more efficiently with less power, which is an advantage for future human-scale medical applications.
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.
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 | 0.002 | 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 | 0.001 | 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