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Record W4413005058 · doi:10.1177/27325016251362418

Current Patterns in the Scope of Craniofacial Fellowship Training: A Website-Based Analysis

2025· article· en· W4413005058 on OpenAlexaboutno aff
M. Kristine Carbullido, Günther Krause, Aidan W. O’Shea, Caroline C. Bay, Jasmine Craig, Jessica D. Blum, Catharine B. Garland, Daniel Cho

Bibliographic record

VenueFACE · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCraniofacial Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsScope (computer science)CraniofacialTraining (meteorology)Current (fluid)Medical educationComputer sciencePsychologyMedicineGeographyEngineeringProgramming language

Abstract

fetched live from OpenAlex

Background: Craniofacial surgery specializes in the treatment of the craniomaxillofacial skeleton and soft tissues. Historically, craniofacial surgery fellowship programs have most often focused on the treatment of pediatric congenital anomalies. However, the scope of the discipline has evolved, and in a recent survey of early-career craniofacial surgeons, nearly 70% of respondents reported their practice was primarily focused on adult patients. The purpose of this study is to systematically analyze the conditions and procedures advertised on craniofacial fellowship websites to ascertain the scope of training opportunities currently available within craniofacial surgery fellowship programs. Methods: In November 2024, the American Society of Craniofacial Surgeons’ (ASCFS) Fellowship Directory was used to identify endorsed craniofacial fellowships in the United States and Canada. Each program website was evaluated for the medical conditions and operative procedures or techniques to which trainees would be exposed. Results: The search identified 36 ASCFS endorsed fellowships, all of which had a website available. From the 34 websites that listed conditions and/or procedures to which trainees are exposed, 69 themes were elucidated. The top 10 themes were cleft lip and palate (91%), craniosynostosis (85%), orthognathic/jaw deformity surgery (77%), acute and secondary trauma reconstruction (71%), pediatric craniofacial surgery (68%), pediatric plastic surgery (56%), microsurgery or free flap reconstruction (56%), distraction osteogenesis (50%), vascular anomalies (47%), and craniofacial syndromes (41%). The least reported themes were neuroplastic reconstruction, tooth extraction, canthopexy, facelift, fat grafting, torticollis, transplant surgery, congenital chest, muscle reinnervation, bone substitutes, adult facial reconstruction, dermatology, preservation rhinoplasty, adult reconstruction, and surgically assisted rapid palatal expansion. Conclusions: There is a discrepancy between the training advertised on ASCFS-endorsed program websites and what recent craniofacial fellowship graduates report practicing. Increasing exposure to non-pediatric craniofacial surgery may better prepare graduates for practice in the evolving landscape of craniofacial surgery.

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 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)0.000
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 score0.021
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.017
GPT teacher head0.303
Teacher spread0.286 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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