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Record W1997234859 · doi:10.1080/15402002.2011.557989

Event-Related Potentials During the Transition to Sleep for Individuals With Sleep-Onset Insomnia

2011· article· en· W1997234859 on OpenAlexafffund
Rona S. Kertesz, Kimberly A. Côté

Bibliographic record

VenueBehavioral Sleep Medicine · 2011
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsBrock University
FundersBrock UniversityNatural Sciences and Engineering Research Council of CanadaUniversity of RochesterUniversity of California, Santa Cruz
KeywordsInsomniaAudiologyOddball paradigmSleep onsetEveningPsychologySleep (system call)PolysomnographyMorningChronic insomniaEvent-related potentialMedicineElectroencephalographySleep disorderPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Event-related potentials may be applied to directly measure information-processing deficits associated with the problem of insomnia. This study is a systematic investigation of cortical hyperarousal during the sleep-onset period in participants with sleep-onset insomnia complaints. Thirteen poor sleepers and twelve good sleepers (GS) were administered an oddball task while awake in the morning and evening and during repeated sleep-onset attempts. Participants signaled detection of a higher pitch target tone as they fell asleep. P2 amplitude was significantly smaller for poor sleepers compared to GS, following standard stimuli at all fronto-central sites, in the pre-sleep waking period at sleep onset. Groups did not differ for N1, N350, or P300 in wake, Stage 1, or Stage 2. The smaller P2 indicates that poor sleepers failed to inhibit the irrelevant standard stimuli. This hyper-attentiveness may explain chronic problems with sleep initiation and could be the target of behavioral and pharmaceutical treatment strategies.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.065
GPT teacher head0.329
Teacher spread0.264 · 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
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

Citations28
Published2011
Admission routes2
Has abstractyes

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