Computer 3D controlled bacterial transports and aggregations of microbial adhered nano-components
Bibliographic record
Abstract
Bacteria can be used as microcarriers for the transport of nano-components. By exploiting specific taxes such as chemotaxis, aerotaxis or phototaxis, to name but a few examples, sensory-based transports of nano-components towards or away from a specific source of chemical, oxygen, or light for instance, can be achieved. Using microbial adhesion methods, such nano-components can be attached to the surface of magnetotactic bacteria (MTB), allowing for precise magnetotaxis computer controlled transport of these nano-components along a planned path on a planar surface or towards a specific region within a 3D space. Here, the possibility of attaching a large number of nano-components to the surface of magnetotactic bacteria combined with the possibility of aggregating a large number of cells in a 3D space suggests the possibility of delivering and aggregating a large number of nano-components at a specific region within a relatively large 3D space using relatively low electrical energy.
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.
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) | 0.000 | 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) | 0.004 | 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".