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Record W3080320987

Deep brain stimulation for drug-resistant epilepsy : efficacy and mechanism of action

2020· dissertation· en· W3080320987 on OpenAlexfundno aff
Mathieu Sprengers

Bibliographic record

VenueGhent University Academic Bibliography (Ghent University) · 2020
Typedissertation
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsnot available
FundersFonds Spéciaux de RechercheUniversiteit GentVlaamse regeringUniversitair Ziekenhuis GentFonds Wetenschappelijk OnderzoekUniversity of Lethbridge
KeywordsEpilepsyNeuroscienceStimulationDeep brain stimulationMechanism (biology)Drug Resistant EpilepsyMedicineDrugDrug actionBrain stimulationMechanism of actionAction (physics)PsychologyPharmacologyInternal medicineChemistryPhysics
DOInot available

Abstract

fetched live from OpenAlex

Recent advances in predicting and preventing epileptic seizures (2013): 42-60.Invasive brain stimulation has emerged as an alternative treatment for refractory epilepsy patients and an increasing number of trials evaluating its efficacy and safety have been published.Various brain structures have been targeted, including the cerebellum, the anterior and centromedian thalamic nucleus, the hippocampus, the ictal onset zone and the subthalamic and caudate nucleus.The rationale for each of these targets and the results obtained in open-label and randomized controlled trials (RCTs) are discussed, with particular emphasis on two large RCTs that investigated open-loop anterior thalamic deep brain stimulation and responsive stimulation of the ictal onset zone.We conclude that promising results have been published for most targets, mainly in open-label trials, and that more RCTs are needed.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.001

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 head0.026
GPT teacher head0.263
Teacher spread0.236 · 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 designTheoretical or conceptual
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
Published2020
Admission routes1
Has abstractno

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