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Record W2594020903 · doi:10.1055/s-0037-1600666

The Future of Intraoperative Neuromonitoring in Skull Base Surgery: Intraoperative Flash Visual Evoked Potentials A Novel Technique Aiming to Reduce the Risk of Intraoperative Visual Pathway Injury

2017· article· en· W2594020903 on OpenAlexaffabout
Fahad Alkherayf, Idara Edem, David Houlden, Chantal Turgeon, Shaun Kilty, Charles Agbi, André Lamothe

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2017
Typearticle
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineOptic nerveVisual systemEvoked potentialSkullSurgeryVisual cortexOphthalmologyNeurosciencePsychologyAudiology

Abstract

fetched live from OpenAlex

Intraoperative optic nerve/chiasmal injury is one the most devastating unexpected outcomes that may happen to patients undergoing endoscopic skull base surgery. Additionally, one of the main goals for most endoscopic skull base surgery is visual improvement, however currently there is limited ability of intraoperative monitoring for the visual pathway. We examine a novel technique which was developed in our center for monitor the visual pathway intraoperatively using continuous flash visual evoked potentials (FVEPs). The FVEPs provide continuous monitoring of the visual pathway including the optic nerve, optic chiasm, optic radiation, and visual cortex, as well as retina function. This technique has been developed at the Ottawa Hospital.

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)0.007
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.036
GPT teacher head0.312
Teacher spread0.276 · 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 designBench or experimental
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
Published2017
Admission routes2
Has abstractyes

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