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Record W4391990693 · doi:10.1055/s-0044-1780358

Dual Surgeon Four-Handed Technique for Open Skull Base Surgery: A Technical and Nontechnical Guide and Systematic Review

2024· article· en· W4391990693 on OpenAlexaff
Jeremy Kam, Fidel Toomey, Celine Hounjet, Seika Taniguchi, Serge Makarenko, Sandra Li, Tony Goldschlager, Ryojo Akagami

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2024
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Surgical Oncology
Canadian institutionsVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsSkullBase (topology)Computer scienceMedicineDual (grammatical number)SurgeryOrthodonticsMedical physicsArtMathematics

Abstract

fetched live from OpenAlex

Introduction: Interdisciplinary and intradisciplinary collaboration is common in skull base neurosurgery owing to the complex, challenging and potentially arduous tumors that require resection. Four handed setups, techniques and working relationships that are common in endoscopic skull base and other disciplines of neurosurgery can be applied to open skull base resections. Four handed open skull base surgery has been the preferred practice for decades at our institution. While this approach is not novel by any means, there continues to be a scarcity of comprehensive written, technical manuals that outline optimal surgical set up, equipment, specific technique, interpersonal relationships, advantages, disadvantages and complications that can arise. Additional barriers to application of this technique include a lack of objective patient outcome measures. Here we aim to provide a technical and nontechnical guide addressing these areas for four handed skull base techniques from two international academic skull base groups and perform a systematic review of available literature regarding four-handed cranial neurosurgery.

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)0.013
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.086
GPT teacher head0.350
Teacher spread0.265 · 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.

Study designNot applicable
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
Published2024
Admission routes1
Has abstractyes

Explore more

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