Combining Aggregates of Synthetic Microscale Nanorobots with Swarms of Computer-controlled Flagellated Bacterial Robots to Enhance Target Therapies Through the Human Vascular Network
Bibliographic record
Abstract
Abstract—The field of medical nanorobotics exploits nanometer-scale components and phenomena to enable new or at least to enhance existing medical diagnostic and interventional procedures. The best route for such miniature robots to access the various regions inside the human body is certainly the vascular network which is constituted of nearly 100,000 km of blood vessels. The variations in blood vessels diameters from a few millimeters in the arteries, down to ~4 µm in the capillaries with respective important variations in blood flow velocities, lead to significant challenges in the development of a robot relying on a singe type of propulsion method while being trackable in the human body. This tracking feasibility in a living body was realized experimentally by integrating magnetic nanoparticles (MNP) capable of creating a net field inhomogeneity that could be detected by
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How this classification was reachedexpand
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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".