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Record W2028897182 · doi:10.1111/jsr.12286

Infrequent dream recall associated with low performance but high overnight improvement on mirror‐tracing

2015· article· en· W2028897182 on OpenAlexafffund
Gaëlle Dumel, Michelle Carr, Louis‐Philippe Marquis, Cloé Blanchette‐Carrière, Tyna Paquette, Toré Nielsen

Bibliographic record

VenueJournal of Sleep Research · 2015
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsCanadian Sleep & Circadian NetworkUniversité de MontréalHôpital du Sacré-Cœur de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDreamPsychologyRecallTask (project management)EveningSleep (system call)AudiologyEye movementCognitive psychologyMorningNeuroscienceMedicineComputer science

Abstract

fetched live from OpenAlex

Although sleep facilitates learning and memory, the roles of dreaming and habitual levels of recalling dreams remain unknown. This study examined if performance and overnight improvement on a rapid eye movement sleep-sensitive visuomotor task is associated differentially with habitually high or low dream recall frequency. As a relation between dream production and visuospatial skills has been demonstrated previously, one possibility is that frequency of dream recall will be linked to performance on visuomotor tasks such as the Mirror Tracing Task. We expected that habitually low dream recallers would perform more poorly on the Mirror Tracing Task than would high recallers and would show less task improvement following a night of sleep. Fifteen low and 20 high dream recallers slept one night each in the laboratory and performed the Mirror Tracing Task before and after sleep. Low recallers had overall worse baseline performance but a greater evening-to-morning improvement than did high recallers. Greater improvements in completion time in low recallers were associated with Stage 2 rather than rapid eye movement sleep. Findings support the separate notions that dreaming is related to visuomotor processes and that different levels of visuomotor skill engage different sleep- and dream-related consolidation mechanisms.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.166
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.127
GPT teacher head0.351
Teacher spread0.224 · 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 teacher head, 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

Citations21
Published2015
Admission routes2
Has abstractyes

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