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Record W2041081418 · doi:10.1159/000350525

Update on Body Composition and Bone Density in Children with Prader-Willi Syndrome

2013· article· en· W2041081418 on OpenAlexaff
Daniela A. Rubin, Natalia Cano Sokoloff, Diobel L. Castner, Daniel A. Judelson, Pamela Wright, Andrea T. Duran, Andrea M. Haqq

Bibliographic record

VenueHormone Research in Paediatrics · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Syndromes and Imprinting
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLean body massMedicineInternal medicineEndocrinologyBone mineralObesityFat massBone densityBody fat percentageBody weightOsteoporosis

Abstract

fetched live from OpenAlex

AIM: To compare body composition in children with Prader-Willi syndrome (PWS) not naïve to growth hormone (GH) with obese and lean controls. METHODS: Participants included 12 children with PWS, 12 children with obesity (body fat percentage >95th percentile for age and sex) and 12 lean children (body fat percentage <85th percentile for age and sex) matched by age and height. Fat mass, lean mass, bone mineral content (BMC), bone mineral density (BMD) and BMD z-score for total body, hips and lumbar spine were obtained through dual X-ray absorptiometry. RESULTS: PWS had higher fat percentage in the legs (p = 0.04) but similar leg fat mass (p = 1.00) compared to obese. PWS exhibited lower lean mass in the body (p = 0.04) and legs (p = 0.02) than obese, but similar to lean (p = 1.00 and p = 0.89, respectively). PWS had lower hip BMC (p < 0.01), BMD (p < 0.01) and BMD z-score (p < 0.01) compared to obese but similar to lean. No other differences were found between PWS and obese (p > 0.05 for all). CONCLUSIONS: Children with PWS not naïve to GH present differences in fat and lean mass distribution compared to obese controls. BMC and BMD appear unaffected by PWS, except at the hips.

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)0.001
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 score0.046
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.015
GPT teacher head0.269
Teacher spread0.254 · 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 designObservational
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

Citations23
Published2013
Admission routes1
Has abstractyes

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