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Record W2342916166 · doi:10.14740/jmc.v7i5.2471

Postoperative Myoclonus After Epilepsy Surgery: A Case Report

2016· article· en· W2342916166 on OpenAlexvenueno aff
Maryam Khaleghi Ghadiri, Christoph Kellinghaus, Mohsen Aghaee Hakak, Ali Goji, Walter Stummer

Bibliographic record

VenueJournal of Medical Cases · 2016
Typearticle
Languageen
FieldMedicine
TopicGlycogen Storage Diseases and Myoclonus
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMyoclonusClonazepamMyoclonic JerkEpilepsy surgeryEpilepsyAnesthesiaElectroencephalographyProgressive myoclonus epilepsyRefractory (planetary science)SurgeryPsychiatry

Abstract

fetched live from OpenAlex

Accurate diagnosis of myoclonus after epilepsy surgery is important to determine the surgical outcome in patients with intractable epilepsy. Emerged bilateral myoclonus in a 53-year-old man after surgical resection for treatment of traumatic refractory epilepsy is reported. An electroencephalography correlate of the myoclonic jerks with cortical potentials was not observed. Treatment with clonazepam significantly reduced the myoclonic twitching. The possible mechanism and differential diagnosis between non-epileptic and epileptic myoclonus following brain surgery are discussed. To avoid misdiagnosis and ensure appropriate treatment, the origin of jerking mimicking epileptic myoclonus after brain surgeries needs to be carefully investigated. J Med Cases. 2016;7(5):164-167 doi: http://dx.doi.org/10.14740/jmc2471w

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)0.001
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0040.000

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 head0.024
GPT teacher head0.309
Teacher spread0.285 · 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 designCase report
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
Published2016
Admission routes1
Has abstractyes

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