A Novel Mohs Precision Tool
Bibliographic record
Abstract
BACKGROUND: Effective treatment by Mohs micrographic surgery requires preparation of high-quality slides. OBJECTIVE: To examine a novel tissue alignment device designed to address variability in tissue processing because of excessive sample trimming. MATERIALS AND METHODS: A device was designed to account for angular errors and unparalleled tissue embedding. A retrospective chart review was performed both with and without the use of the device over the course of a 4-year period (2012-2015). RESULTS: Between January 1, 2012, and June 10, 2014, before device implementation, mean number of stages per case was 1.65 (n = 3,680) and mean number of surgeries per day was 6.34 (n = 640). Between June 11, 2014, and October 02, 2015, with device implemented, the average number of stages per case between decreased to 1.58 (n = 2,562) and the number of daily surgeries increased to 7.05 (n = 358). This represents a significant decrease in number of stages per case by 0.07 stages (95% CI: -0.01 to -0.13, p = .02), as well as an increase in the number of cases per day by 0.71 cases (95% CI: 0.12-1.3, p < .01). CONCLUSION: Slide preparation using the novel alignment device may result in less tissue waste and more cases being performed daily.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".