Translocation of links through a pore: effects of link complexity and size
Bibliographic record
Abstract
Abstract We have used Langevin dynamics to simulate the forced translocation of linked polymer rings through a narrow pore. For fixed size (i.e. fixed number of monomers) the translocation time depends on the link type and on whether the rings are knotted or unknotted. For links with two unknotted rings the crossings between the rings can slow down the translocation and are responsible for a delay as the crossings pass through the pore. The results fall on a set of relatively smooth curves for different link families with the translocation time not always increasing with crossing number within the same family. When one ring is knotted the results depend on whether the link is prime or composite and, for the composite case, they depend on whether the knotted or unknotted ring enters the pore first. We find a similar situation for 3-component links where the results depend on whether the link is prime or composite. These results contribute to our understanding of how the entanglement complexity between filaments impacts their translocation dynamics and should be useful for extending nanopore-sensing techniques to probe the topological properties of these systems.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".