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Record W2034294964 · doi:10.4021/jnr.v2i6.173

The New Antiepileptic Drugs or the Traditional Antiepileptic Drugs? Update in Terms of Drug Side Effects

2013· article· en· W2034294964 on OpenAlexvenueno aff
İbrahim Bora, Aylin Bican Demir

Bibliographic record

VenueJournal of Neurology Research · 2013
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsLevetiracetamMedicineEpilepsyAntiepileptic drugPhenytoinValproic AcidDrugAdverse effectSide effect (computer science)Depression (economics)Intensive care medicinePharmacologyAnesthesiaPsychiatry

Abstract

fetched live from OpenAlex

Epilepsy is defined as episodic cerebral dysfunction due to increased excitability of brain cells that caused by various reasons. Anti-epileptic drugs (AED) cannot stop the mechanisms that cause epilepsy, but they can decrease the frequency of seizures or completely stop the seizures without causing a general depression in central nervous system while they are using. In this case report, we aimed to discuss the therapeutic way that physician chose, depending on personal experiences in patient that developed adverse effects to both old generation (phenytoin, valproic acid) and new generation (Vaigabatrine, Lamotirgine, Levetiracetam, Pregabaline) AEDs. Even though it needs to be careful when treating a patient with epilepsy to maximize the therapeutic efficacy and to prevent complications, we intended to emphasise that there are unknown parts of AED mechanisms. doi: http://dx.doi.org/ 10.4021/jnr167e

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.041
GPT teacher head0.347
Teacher spread0.307 · 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
Published2013
Admission routes1
Has abstractyes

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