MétaCan
Menu
Back to cohort
Record W3153201461 · doi:10.1177/15357597211004549

Proceedings of the Sleep and Epilepsy Workshop: Section 2 Comorbidities: Sleep Related Comorbidities of Epilepsy

2021· article· en· W3153201461 on OpenAlexaff
Milena Pavlova, Marcus Ng, Rebecca M. Allen, Mélanie Boly, Sanjeev V. Kothare, Hiten Zaveri, Phyllis C. Zee, Gail K. Adler, Gordon F. Buchanan, Mark Quigg

Bibliographic record

VenueEpiliepsy currents/Epilepsy currents · 2021
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of Manitoba
FundersBAND foundation
KeywordsEpilepsySleep (system call)Sleep medicineMedicineComorbidityWorkgroupCircadian rhythmSleep disorderPsychiatryNeurosciencePsychologyInsomniaComputer science

Abstract

fetched live from OpenAlex

Epilepsy is a chronic disease with multiple, complex comorbidities. Bidirectional relationships exist among seizures, sleep, circadian rhythms, and diseases within and outside of the central nervous system. Seizures fragment sleep and can contribute to development of sleep disorders, which in turn leads to worse overall health and more seizures. Moreover, treatment options are often limited by interactions with anti-seizure medications. Advances in the fields of epilepsy and in sleep medicine have been made separately, and therefore treating patients with these comorbidities necessitates interdisciplinary approach. The focus of this section of the Sleep and Epilepsy Workgroup was to identify methods of collaboration and outline investigational, educational, and treatment priorities to mutually advance what we consider a combined field.

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)0.008
metaresearch head score (Gemma)0.008
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0050.004
Open science0.0020.006
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0350.012

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 head0.025
GPT teacher head0.291
Teacher spread0.266 · 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
GenreOther

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

Citations13
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueEpiliepsy currents/Epilepsy currentsSame topicEpilepsy research and treatmentFrench-language works237,207