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Record W2609898829 · doi:10.1093/sleepj/zsx050.400

0401 DREAM INCORPORATION OF INSOMNIA SUFFERERS AND GOOD SLEEPERS IN AN EXPERIMENTAL SETTING

2017· article· en· W2609898829 on OpenAlexaff
Christine Rancourt, Jonathan Charest, Maude Pedneault-Drolet, Alexandra D. Pérusse, C.H. Bastien

Bibliographic record

VenueSLEEP · 2017
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsUniversité Laval
FundersNational Research Foundation of KoreaMinistry of Science, ICT and Future PlanningNational Research Foundation
KeywordsDreamPsychologySleep (system call)NightmareWakefulnessInsomniaAudiologyClinical psychologyPsychiatryMedicinePsychotherapistElectroencephalography

Abstract

fetched live from OpenAlex

Dream incorporation in laboratory setting manifests itself by direct (ex: experimenter, electrodes, etc) or indirect (ex: participating in an experiment) presence of elements referencing to the experimental setting. The presence of increased cortical activation during sleep and wakefulness in insomnia sufferers (INS) is well documented and is often reflected through enhanced information processing. This latter could increase awareness of sleeping environments and lead to dream incorporation of the experimental settings. The objective of the present study is to compare INS and good sleepers (GS) regarding dream incorporation for laboratory settings. PSG was recorded in 12 INS and 12 GS (aged 30 to 45) for five consecutive nights (N1 to N5). On N3 and N5, participants were awoken during REM periods for dream collection. Dream incorporation of the laboratory setting was targeted with the following categories: environment (bed, electrodes, etc.) staff and experience (being awakened, report dreams, etc.). Dream elements referring to sleep but not related to laboratory settings were also quantified. Independent sample T tests were used to assess between groups differences in regards to 1) Environment 2) Staff 3) Experience and 4) Sleep dream incorporation. Two participants were excluded due to extreme data. Results showed a significant difference between INS and GS for environmental dream incorporation (p=.001), INS reporting more environmental elements. No significant difference were found for Staff (p=.483), Experience (p=.289) and Sleep (p=.283). Because a greater number of elements from the laboratory environment is observed in INS’ dreams, it might suggest that INS are more hyperaroused at sleep onset and display enhanced information processing. Results also suggest that INS appeared more mindful of their surroundings since the immediate, concrete, external elements of the environment are more prone to be treated and so, incorporated in dreams. CIHR (86571).

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.050
GPT teacher head0.342
Teacher spread0.292 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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