Glyconanosynthons as powerful scaffolds and building blocks for the rapid construction of multifaceted, dense and chiral dendrimers
Bibliographic record
Abstract
This review represents the first of its kind in that it is mainly devoted to the use of carbohydrates as both scaffolds and building blocks for the construction of a wide range of novel, dense, and chiral dendrimers. It deviates from several previous reviews describing solely carbohydrates as functional surface groups, mostly devoted to biological applications. A brief overview of the most recent synthetic strategies in dendrimer design will be presented for the purpose of comparing their differences, similitudes, and advantages. A particular emphasis will be devoted to the general family of core molecules or scaffolds possessing a large number of functional groups from which, carbohydrates clearly emanate for their wide structural diversities, abundant chiral centers, and the relative ease with which their functional groups can be selectively manipulated. This beneficial characteristic relies on the fact that carbohydrates exist in enantiomeric states, several conformations, anomeric configurations, range of functional groups, and as three to seven carbon units.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".