Modification of the Vancouver Scar Scale (VSS) score for Scarring Assessment using Rattus novergicus Abnormal Scar Model
Bibliographic record
Abstract
The abnormal scar is a unique fibrosis disease because it only occurs in humans (Homo sapiens). Researchers now challenge no other animal species, including primates, are found to naturally form scar7, whereas animal models are essential references for human treatment modalities. This study aimed to determine the Modified Vancouver Scar Scale (VSS) score with the addition of collagen density parameters used to assess the scar in experimental animals quantitatively and generates a better assessment of the scar. The cross-sectional analytical survey method was adopted. The experimental animal was Rattus novergicus. The Modified VSS score was applied to assess the normal and abnormal scar data. The Likert categorization guidelines were used to obtain the VSS Score modification score. The collagen density and VSS had a significantly different based on T-test (p <0.05). The differences were also shown by the control and treatment groups. On the correlation analysis, there were the positive coefficient (0.722). The result can be described that the collagen density increases, when the VSS score is high. It also showed the differences based on the score (p <0.05). The Modified VSS score calculation's final results are classified into three groups namely Good (ranged from 0 to 1); Medium (ranged from 2 to 4); and Adverse (ranged from 5 to 6). The Modified VSS score is possibly to be used for the scar assessment to the Rattus novergicus abnormal scar model.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".