Reliability of the Patient and Observer Scar Assessment Scale in Evaluating Linear Scars after Thyroidectomy
Bibliographic record
Abstract
OBJECTIVE: To compare the reliability of the Patient and Observer Scar Assessment Scale (POSAS) with the Vancouver Scar Scale (VSS) in evaluating thyroidectomy scars. METHODS: At 6 months after the operation, 112 patients who underwent thyroid surgery via collar neck incision were evaluated by two blinded plastic surgeons and two senior residents using the VSS and the observer component of the POSAS. In addition, the observer-reported VAS score and patient-reported Likert score were evaluated. Internal consistency, interobserver reliability, and correlations between the patient- and observer-reported outcomes were examined. RESULTS: The observer component of POSAS scores demonstrated higher internal consistency and interobserver reliability than the VSS. However, the correlations between the observer-reported VAS score and the patient-reported Likert score (0.450) and between the total sum of patient and observer component scores (0.551) were low to moderate. CONCLUSIONS: The POSAS is more consistent over repeated measurements; accordingly, it may be considered a more objective and reliable scar assessment tool than the VSS. However, a clinician's perspective may not exactly match the patient's perception of the same scar.
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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 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".