Preparation and characterization of blends of star-poly(ε-caprolactone-co-D,L-lactide) and oligo(ε-caprolactone)
Bibliographic record
Abstract
Polymer blending provides a relatively facile means of combining the separate desirable properties of different polymers into a single material. In this paper blends of a low-molecular-weight star co-polymer of epsilon-caprolactone and D,L-lactide with a linear oligo(epsilon-caprolactone) are prepared and characterized as a possible biodegradable injectable drug-delivery vehicle. The melting characteristics, melt viscosity and degree of crystallinity of the blends were measured, and an in vitro degradation study was performed over a period of 12 weeks. The blends all had a single glass transition temperature and an onset of melting point near body temperature, with the melting point range decreasing as the star co-polymer content increased. The melt viscosity of the blends increased as the star co-polymer content increased, in a manner consistent with miscible blend behavior. The star co-polymer degraded fastest, with a more than 60% mass decrease over the 12-week period. As the oligo(epsilon-caprolactone) content increased, the degradation rate decreased, with the oligo(epsilon-caprolactone) exhibiting a mass loss of only 12% over the 12-week period.
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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) | 0.000 | 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 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".