A reliable frozen section technique for basal cell carcinomas of the head and neck
Bibliographic record
Abstract
Basal cell carcinomas (BCCs) of the head and neck treated by conventional techniques of surgical excision, curettage, cryotherapy and radiation therapy have recurrence rates of up to 42%. Mohs micrographic surgery (MMS) decreases the recurrence rate but can be expensive, delay definitive reconstruction and is limited in its availability. The authors report a series of 50 patients with head and neck BCCs treated by a surgeon-directed 'en face' frozen section technique that immediately evaluates the entire peripheral and deep margins during BCC resection, and potentially offers a more efficient and equally effective alternative to MMS. Patient demographics, pathology results, operative time, technique and outcomes are all reported. With a mean follow-up of three years, there was only one recurrence (1.7%). Mean total operative time was 1 h 47 min. The authors conclude that this surgeon-directed 'en face' frozen section technique does not require any specialized training, enables more rapid and reliable results than standard frozen section techniques that are currently used, and provides outcomes equivalent to MMS in the surgical treatment of head and neck BCCs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".