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Record W4210627700 · doi:10.3390/ctn6010003

The Parasomnias and Sleep Related Movement Disorders—A Look Back at Six Decades of Scientific Studies

2022· article· en· W4210627700 on OpenAlexaff
Roger Broughton

Bibliographic record

VenueClinical and Translational Neuroscience · 2022
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSleepwalkingParasomniaSleep paralysisPsychologyNon-rapid eye movement sleepRestless legs syndromeSleep disorderDystoniaSleep (system call)NightmareInsomniaMedicinePsychiatryElectroencephalographyExcessive daytime sleepiness

Abstract

fetched live from OpenAlex

The objective of this article is to provide a comprehensive personal survey of all the major parasomnias with coverage of their clinical presentation, investigation, physiopathogenesis and treatment. These include the four major members of the slow-wave sleep arousal parasomnias which are enuresis nocturna (bedwetting), somnambulism (sleepwalking), sleep terrors (pavor nocturnus in children, incubus attacks in adults) and confusional arousals (sleep drunkenness). Other parasomnias covered are sleep-related aggression, hypnagogic and hypnopompic terrifying hallucinations, REM sleep terrifying dreams, nocturnal anxiety attacks, sleep paralysis, sleep talking (somniloquy), sexsomnia, REM sleep behavior disorder (RBD), nocturnal paroxysmal dystonia, sleep starts (hypnic jerks), jactatio capitis nocturna (head and total body rocking), periodic limb movement disorder (PLMs), hypnagogic foot tremor, restless leg syndrome (Ekbom syndrome), exploding head syndrome, excessive fragmentary myoclonus, nocturnal cramps, and sleep-related epileptic seizures. There is interest in the possibility of relationships between sleep/wake states and creativity.

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)0.004
metaresearch head score (Gemma)0.007
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: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0100.008
Science and technology studies0.0010.003
Scholarly communication0.0040.008
Open science0.0010.002
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0020.001

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 head0.129
GPT teacher head0.389
Teacher spread0.260 · 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
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

Citations3
Published2022
Admission routes1
Has abstractyes

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