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Record W2773732447 · doi:10.1093/ons/opx245

Operative Nuances of Stereotactic Leksell Frame-Based Depth Electrode Implantation

2017· article· en· W2773732447 on OpenAlexaff
Holger Joswig, Carolyn Benson, Andrew G. Parrent, Keith W. MacDougall, David A. Steven

Bibliographic record

VenueOperative Neurosurgery · 2017
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Background: For intracranial electroencephalographic monitoring, stereotactically implanted depth electrodes are increasingly used at epilepsy centers around the world. Objective: To identify pearls and pitfalls from our experience with stereotactic Leksell (Elekta AB, Stockhom, Sweden) frame-based depth electrode implantation. Methods: An intraoperative video of the implantation technique was recorded. Results: A detailed description and a video on how to implant depth electrodes using the stereotactic Leksell frame is provided. Conclusion: Neurosurgeons implanting depth electrodes for intracranial electroencephalographic monitoring might find the technical nuances and caveats described in this technical note useful for their practice.

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)0.005
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.040
GPT teacher head0.344
Teacher spread0.304 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations20
Published2017
Admission routes1
Has abstractyes

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