Analysis of Frequency of Use of Different Scar Assessment Scales Based on the Scar Condition and Treatment Method
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Analysis of scars in various conditions is essential, but no consensus had been reached on the scar assessment scale to select for a given condition. We reviewed papers to determine the scar assessment scale selected depending on the scar condition and treatment method. We searched PubMed for articles published since 2000 with the contents of the scar evaluation using a scar assessment scale with a Journal Citation Report impact factor >0.5. Among them, 96 articles that conducted a scar evaluation using a scar assessment scale were reviewed and analyzed. The scar assessment scales were identified and organized by various criteria. Among the types of scar assessment scales, the Patient and Observer Scar Assessment Scale (POSAS) was found to be the most frequently used scale. As for the assessment of newly developed operative scars, the POSAS was most used. Meanwhile, for categories depending on the treatment methods for preexisting scars, the Vancouver Scar Scale (VSS) was used in 6 studies following a laser treatment, the POSAS was used in 7 studies following surgical treatment, and the POSAS was used in 7 studies following a conservative treatment. Within the 12 categories of scar status, the VSS showed the highest frequency in 6 categories and the POSAS showed the highest frequency in the other 6 categories. According to our reviews, the POSAS and VSS are the most frequently used scar assessment scales. In the future, an optimal, universal scar scoring system is needed in order to better evaluate and treat pathologic scarring.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 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 it