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Record W4214885476 · doi:10.1055/s-0042-1743724

Utilization of Intraoperative Continuous Flash Visual Evoked Potentials in Endoscopic Skull Base Surgery

2022· article· en· W4214885476 on OpenAlexaff
Rafael Ochoa-Sanchez, Mazen Alotaibi, Shaun Kilty, Charles Agbi, André Lamothe, David Schramm, Fahad Alkherayf

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2022
Typearticle
Languageen
FieldMedicine
TopicIntraoperative Neuromonitoring and Anesthetic Effects
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsSkullMedicineSurgerySAFERComputer science

Abstract

fetched live from OpenAlex

Objective: Minimally invasive endoscopic endonasal skull base surgery offer safer and more effective access to the skull base to remove benign and malignant tumors. However, endoscopic skull base surgery around the visual pathway may increase the risk of injury of the visual pathway. Monitoring of flash visual evoked potentials (FVEPs) during surgery may detect a possible injury to the visual pathway, allowing the surgeon to take corrective measures during surgery to reverse or minimize it. The purpose of this study is to determine whether monitoring FVEPs during brain surgery can predict, prevent or minimize visual pathway injury.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.049
GPT teacher head0.299
Teacher spread0.250 · 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 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
Published2022
Admission routes1
Has abstractyes

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