Robust, anti-biofouling 2D nanogel films from poly(<i>N</i>-vinyl caprolactam-<i>co</i>-vinylimidazole) polymers
Bibliographic record
Abstract
quaternization to form the nanogels. The swelling ratio of the gels was precisely controlled by regulating the inter-chain spacing of the polymers at the level of the carbon atom chain length of the cross-linker. The short-chain alkanes used are relatively rigid and their dimensions provide an accurate estimate of the chain spacing in the nanogels. It was shown that small differences in the carbon atom number of the cross-linking agent led to significant differences in the mechanical properties of the nanogels, in particular in the softness, deformability, and contact area (in film form), all of which increased with increasing carbon number. Films of the softer gels not only showed good adhesion to a number of substrates, but were also mechanically robust. In addition, the films showed excellent light transmission and nontoxicity to L929 cells. Nanogels of intermediate softness were shown to inhibit the adhesion of bacteria and human umbilical vein smooth muscle cells (HUVSMCs), and to be resistant to the adsorption of the plasma protein fibrinogen, indicating strong anti-biofouling properties. Gels that were either too stiff or too soft showed somewhat weaker anti-fouling activity in terms both of HUVSMCs adhesion and protein adsorption.
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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 | 0.000 |
| 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) | 0.001 | 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".