Preparation and mechanical properties of poly(chitosan‐<i>g</i>‐<scp>DL</scp>‐lactic acid) fibrous mesh scaffolds
Bibliographic record
Abstract
Abstract DL‐lactic acid was grafted onto chitosan to produce poly(chitosan‐g‐DL‐lactic acid)(PCLA) without using a catalyst. These PCLAs were then spun into filaments and further fabricated into fibrous mesh scaffolds using an improved wet‐spinning technique. The diameter of filaments in different scaffolds could vary from a few micrometers to several tens of micrometers. The scaffolds exhibited various pore sizes ranging from about 20 µm to more than 200 µm and different porosities up to 80%. The several main processing conditions were optimized for obtaining the desired scaffolds with well‐controlled structures. The tensile and compressive mechanical properties of the mesh scaffolds in both dry and hydrated states were mainly examined. Significantly improved tensile strength and modulus, enhanced compressive modulus, and stress as well as the dimensional stability for these mesh scaffolds in their hydrated state were observed. Copyright © 2007 John Wiley & Sons, Ltd.
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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".