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Record W1986262285 · doi:10.1037/h0087343

The mismatch negativity to frequency deviants during the transition from wakefulness to sleep.

2000· article· en· W1986262285 on OpenAlexaff
Merav Sabri, Duncan R. de Lugt, Kenneth B. Campbell

Bibliographic record

VenueCanadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale · 2000
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMismatch negativityWakefulnessPsychologyAudiologyUnconsciousnessElectroencephalographyContingent negative variationStimulus (psychology)Vigilance (psychology)Sleep (system call)Non-rapid eye movement sleepDevelopmental psychologyCognitive psychologyNeurosciencePsychiatryMedicine

Abstract

fetched live from OpenAlex

This study examines the changes in the Mismatch Negativity during the transition from a waking, conscious state to one of sleep and unconsciousness. Auditory event-related potentials were recorded from eight participants during the sleep onset period. A 1,000 Hz-standard stimulus was presented every 600 ms. At random, on 20% of the trials, the standard was changed to either a large 2,000-Hz or a small 1,100-Hz deviant. During wakefulness, the large deviant elicited a larger, long-lasting MMN than the small deviant. Following the large deviant during relaxed wakefulness and Stage 2 sleep, the MMN continued to be elicited although it was reduced in amplitude. No significant MMN was recorded for either deviant in Stages 1 and slow wave sleep. The loss of consciousness therefore appears to have a marked effect on the MMN.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.039
GPT teacher head0.301
Teacher spread0.262 · 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 designBench or experimental
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
Published2000
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentaleSame topicNeuroscience and Music PerceptionFrench-language works237,207