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Record W2070588170 · doi:10.1080/15402002.2013.854245

Conducting Actigraphy Research in Children With Neurodevelopmental Disorders—A Practical Approach

2014· article· en· W2070588170 on OpenAlex
Diane Fawkes, Beth A. Malow, Shelly K. Weiss, Ann Reynolds, Alvin Loh, Karen W. Adkins, Deborah D. Wofford, Amanda Wyatt, Suzanne E. Goldman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBehavioral Sleep Medicine · 2014
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsSurrey Place CentreSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Advancing Translational SciencesU.S. Public Health ServiceVanderbilt University
KeywordsActigraphyAutismAutism spectrum disorderPsychologyTypically developingSession (web analytics)Physical therapyPhysical medicine and rehabilitationMedicineDevelopmental psychologyComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

The literature has been highly informative for when to use actigraphy and its validity in pediatric research. However, minimal literature exists on how to perform actigraphy, especially in special populations. We determined whether providing actigraphy training to parents and coordinators increased the nights of actigraphy data that could be scored. We compared two studies in children with autism spectrum disorders, one of which provided a basic level of training in a single-site trial and the other of which provided more detailed training to parents and coordinators in a multisite trial. There was an increase in scorable nights in the multisite trial containing a one-hour structured parent training session. Our results support the use of educational tools in clinical trials that use actigraphy.

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.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.880

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.209
GPT teacher head0.419
Teacher spread0.210 · 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