Frontispiece: Supramolecular Assembly of Peptide and Metallopeptide Gelators and Their Stimuli‐Responsive Properties in Biomedical Applications
Bibliographic record
Abstract
A fascinating class of soft materials are supramolecular gels which have attracted significant attention in recent years. They are composed of small molecule gelators that assemble into supramolecular network structures. Some gel materials are able to respond to various stimuli making them attractive drug delivery vehicles and as matrices for tissue regeneration. Peptide-based gel materials are particularly attractive as they possess numerous advantages including biocompatibility and biodegradability. Stimuli-responsive peptides that alter properties as a function of pH, redox, temperature, and enzymes offer the potential to create materials with tunable characteristics. Herein, the stimuli-responsive properties (pH, redox, temperature, and enzyme responsive properties), as well as the biocompatible/-degradable nature of the peptide gelators are highlighted, for more details, see the Minireview by H.-B. Kraatz and N. Falcone on page 14316 ff.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.219 | 0.188 |
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".