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Record W2762439591 · doi:10.1139/bcb-2017-0064

Understanding and managing sleep disruption in children with fetal alcohol spectrum disorder

2017· review· en· W2762439591 on OpenAlexaffvenue
Ana Hanlon‐Dearman, Maida Lynn Chen, Heather Carmichael Olson

Bibliographic record

VenueBiochemistry and Cell Biology · 2017
Typereview
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsUniversity of ManitobaResearch ManitobaManitoba Health
Fundersnot available
KeywordsFetal Alcohol Spectrum DisorderSleep (system call)Fetal alcoholAlcoholFetusMedicinePsychologyPsychiatryBiologyPregnancyGeneticsComputer scienceBiochemistry

Abstract

fetched live from OpenAlex

Accumulating evidence has revealed high rates of sleep disruption among children with fetal alcohol spectrum disorder (FASD). Multiple animal and clinical studies have found a clear association between sleep problems and prenatal alcohol exposure, and recent research is beginning to characterize the types and extent of sleep disruption in FASD. Nevertheless, sleep disruption in children with FASD often goes unrecognized or is treated without referring to an evidence base. Children's disrupted sleep interferes with parental sleep and increases caregiver burden, which is of particular importance for families raising children with FASD, a group with very high levels of caregiving stress. The literature supporting an association between sleep problems and deficits in emotional, behavioral, and cognitive function in children is compelling, but needs further investigation in children with FASD. This paper will review the current state of knowledge on sleep in FASD and recommend a rational approach to sleep interventions for affected children and their families.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.853
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.042
GPT teacher head0.300
Teacher spread0.258 · 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 designOther design
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

Citations41
Published2017
Admission routes2
Has abstractyes

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