Rapid and Tunable Reductive Degradation of Disulfide‐Labeled Polyesters
Bibliographic record
Abstract
Abstract A new approach for rapid and tunable degradation of reductively degradable polyesters (ssPESs) with multiple disulfides on the polymer backbones is reported. The approach centers on the control of the amount of disulfides in the synthesis of ssPESs by polycondensation of a disulfide‐containing diacid with various single and mixed diols having different molecular weights and disulfides. The disulfide concentration in ssPESs is tuned by incorporation of diols labeled with disulfides or diols with different MWs. The degradation rate is enhanced with increasing ssPES molecular weight. With ssPESs bearing disulfides positioned repeatedly along the backbone, the rapid and controlled degradation is compared with the slow degradation of polyesters with only a single disulfide in the center.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".