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Record W2997741002 · doi:10.1097/wnp.0000000000000644

A North American History of Cannabis Use in the Treatment of Epilepsy

2019· review· en· W2997741002 on OpenAlexaffabout
Alexandra Carter

Bibliographic record

VenueJournal of Clinical Neurophysiology · 2019
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCannabisEpilepsyLegalizationPsychiatryRecreational DrugMedicineEndocannabinoid systemCannabinoidClinical trialEffects of cannabisRecreationPsychologyDrugPolitical scienceCannabidiolInternal medicineLaw

Abstract

fetched live from OpenAlex

Cannabis has been used for millennia in religious ceremonies, for recreation and for its medicinal qualities. There are multiple accounts detailing the specific ailments cannabis has been used to treat, many of which have included epilepsy. Racial discrimination and political stigmatization led to prohibition, which limited both patients' and researchers' access to the drug through the 20th century. Recently, academic interest has been renewed in cannabis, especially regarding the modulation of cortical excitability via the human endocannabinoid system. Modern research has produced several promising studies regarding the treatment of epileptic encephalopathies. Legalization of marijuana in Canada has potentially allowed for further trials, but it is by no means an end to the controversy surrounding the treatment of epilepsy with cannabinoids.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.197
GPT teacher head0.453
Teacher spread0.256 · 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
GenreReview

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

Citations7
Published2019
Admission routes2
Has abstractyes

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