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Record W1768139681 · doi:10.1684/epd.2007.0095

Chronic PLEDs with transitional rhythmic discharges (PLEDs‐plus) in remote stroke

2007· article· en· W1768139681 on OpenAlexaff
José Francisco Téllez‐Zenteno, Sylaja N. Pillai, Michael D. Hill, Neelan Pillay

Bibliographic record

VenueEpileptic Disorders · 2007
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of CalgaryUniversity of Saskatchewan
Fundersnot available
KeywordsElectroencephalographyRhythmStroke (engine)MedicineEpilepsyAnesthesiaCardiologyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Background. Periodic lateralized epileptiform discharges (PLEDs) are a rare phenomenon in electroencephalography, occurring in acute structural brain lesions. In general, PLEDs appear transiently in acute lesions, but a few reports have described persistent PLEDs in chronic lesions. Case report. An 86-year-old female was admitted, in 1999, with a left MCA stroke associated with right hand focal motor seizures. The first EEG in February of 2002 showed PLEDs over the left hemisphere associated with rhythmic discharges (PLEDs-plus). The patient was admitted on a second occasion in 2003 because of three sequential seizures and the EEG showed a similar pattern. Finally in 2006, the patient was admitted again because of sequential complex partial seizures and an EEG showed the same PLEDS-plus pattern as the EEGs of 2002 and 2003. Discussion. We report an unusual case of chronic PLEDs associated with rhythmic discharges in a patient with recurrent seizures and remote stroke.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.278
Teacher spread0.268 · 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 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

Citations9
Published2007
Admission routes1
Has abstractyes

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