Current and Emerging Options for Documenting Scars and Evaluating Therapeutic Progress
Bibliographic record
Abstract
BACKGROUND: Current studies on pathological scarring often rely on subjective means. The identification and implementation of objective documentation standards are of high priority. OBJECTIVE: To identify, describe, and evaluate current and upcoming options for objective scar documentation. METHODS: The authors analyzed imaging options (ultrasound, PRIMOS, and optical coherence tomography) and scales/questionnaires (Visual Analog Scale, Vancouver Scar Scale, Patient and Observer Scar Assessment Scale, and Dermatology Life Quality Index) based on the existing literature and described their application for scar documentation. RESULTS: A variety of capable options for the documentation of scars are available. None of these, however, seem suitable as a stand-alone tool for scar documentation. CONCLUSION: A combination of objective imaging tools in combination with questionnaires and scar scales may be warranted to achieve comprehensive documentation during everyday clinical work and in regard to a higher level of evidence in future research.
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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 | 0.016 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".