Identification of Shear Modulus of Gelatin Blended with Carboxymethylcellulose Scaffolds Using Curve Fitting Method from Compressive Test
Bibliographic record
Abstract
Biopolymer scaffolds which made from various ratios of gelatin blended with carboxymethylcellulose (CMC) were studied. The scaffolds were fabricated to porous structure via freeze drying process and crosslinked to induce conjugation of free amide and carboxyl groups in protein structures by using thermal crosslinking techniques. The mechanical properties of the scaffolds were characterized by experimental procedure. In order to evaluate the modeling, we described the stress-strain behavior of the scaffolds by fitting the data to a neo-Hookean model. Results shown that models which evaluated CMC blended gelatin scaffold in the ratio of 80 and 20 of gelatin and CMC occurred in the highest average in shear modulus which was 10.30 kPa compared to other blended scaffolds. Gelatin scaffold with 10, 30 and 40% of CMC showed dramatically decreased in the shear modulus which were 2.12, 1.73 and 0.85 kPa, respectively compared to pure gelatin scaffold with significant different. These results showed the possibility of using CMC as a low cost material to combine with biopolymers for using in tissue engineering applications.
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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 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".