Bibliographic record
Abstract
Self‐immolative linear polymers are a recently developed class of materials that typically undergo head‐to‐tail depolymerization in response to the cleavage of stimuli‐responsive end‐caps from their termini. These polymers have been inspired by self‐immolative dendrimers and oligomers that undergo cascades of cyclization and/or elimination reactions in response to the activation or cleavage of a trigger moiety. During the past decade, several backbones have been introduced including polycarbamates, polycarbonates, polythiocarbamates, polythiocarbonates, polyacetals, and poly(benzyl ether)s. These backbones have been tuned to control the depolymerization rate, and end‐caps responsive to stimuli including enzymes, light, heat, acid, and small molecules such as fluoride ions have been incorporated. They have been explored for the development of sensing devices, microcapsules, and nanoscale assemblies such as micelles and vesicles. In these applications, their depolymerization in response to end‐cap cleavage affords effective amplification of these stimuli, resulting in enhanced sensitivity. Their depolymerization kinetics has also been studied in detail. This article will review the development and current status of both the chemistry and application of linear self‐immolative polymers.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".