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Record W2105740232 · doi:10.1002/hed.20656

Craniofacial surgery for nonmelanoma skin malignancy: Report of an international collaborative study

2007· article· en· W2105740232 on OpenAlexaff
Ellie Maghami, Simon G. Talbot, Snehal G. Patel, Bhuvanesh Singh, Ashok Polluri, Patrick G. Bridger, Giulio Cantù, Anthony D. Cheesman, Geraldo De, Paul F. Donald, Luiz Roberto Medina dos Santos, Dan M. Fliss, Patrick Gullane, Ivo P. Janecka, S Kamata, Luiz Paulo Kowalski, Dennis H. Kraus, Paul A. Levine, Sultan Pradhan, Victor L. Schramm, Carl H. Snyderman, WI Wei, Jatin P. Shah

Bibliographic record

VenueHead & Neck · 2007
Typearticle
Languageen
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsMedicineCraniofacialSkin cancerHistologyCraniofacial surgeryMalignancySurgeryOverall survivalBasal cellDermatologyCancerInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: This study examined the efficacy of craniofacial surgery (CFS) in treating locally advanced nonmelanoma skin cancer (NMSC). METHODS: One hundred twenty patients who underwent CFS for NMSC were identified from 17 participating institutions. Patient, tumor, and treatment information was analyzed for prognostic impact on survival. RESULTS: Surgical margins were negative in 74%, close in 3%, and involved in 23% of patients. Complications occurred in 35% of patients, half of which were local wound problems. Operative mortality was 4%. Median follow-up interval after CFS was 27 months. The 5-year overall survival (OS), disease-specific survival (DSS), and recurrence-free survival (RFS) rates were 64%, 75%, and 60%, respectively. Squamous cell histology, brain invasion, and positive resection margins independently predicted worse OS, DSS, and RFS. CONCLUSION: CFS is an effective treatment for patients with NMSC invading the skull base. Histology, extent of disease, and resection margins are the most significant predictors of outcome.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.358
Teacher spread0.328 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2007
Admission routes1
Has abstractyes

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