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Record W2192579701 · doi:10.1177/229255031402200301

A reliable frozen section technique for basal cell carcinomas of the head and neck

2014· article· en· W2192579701 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePlastic Surgery · 2014
Typearticle
Languageen
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsUniversity of ManitobaDalhousie University
Fundersnot available
KeywordsMedicineFrozen section procedureCryotherapyHead and neckSurgeryMohs surgeryBasal cell carcinomaNuclear medicineBasal cellPathology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.234
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it