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Record W2115123766 · doi:10.1002/ppul.10152

Sleep and breathing in Prader‐Willi syndrome

2002· review· en· W2115123766 on OpenAlexaff
Gillian M. Nixon, Robert T. Brouillette

Bibliographic record

VenuePediatric Pulmonology · 2002
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Syndromes and Imprinting
Canadian institutionsMcGill UniversityMontreal Children's Hospital
Fundersnot available
KeywordsMedicinePolysomnographyObstructive sleep apneaPediatricsNon-rapid eye movement sleepHypoventilationHypotoniaSleep apneaAbnormalityExcessive daytime sleepinessApneaSleep disorderAnesthesiaInternal medicineInsomniaRespiratory systemPsychiatryElectroencephalography

Abstract

fetched live from OpenAlex

Prader-Willi syndrome (PWS) is a genetic disorder, with hypotonia being the predominant feature in infancy, and developmental delay, obesity, and behavioral problems becoming more prominent in childhood and adolescence. Children with this disorder frequently suffer from excessive daytime sleepiness and have a primary abnormality of the circadian rhythm of rapid eye movement sleep. They also have primary abnormal ventilatory responses to hypoxia and hypercapnia, and these abnormalities may be exacerbated by obesity. Children with PWS are at risk of a variety of abnormalities of breathing during sleep, including obstructive sleep apnea and sleep-related alveolar hypoventilation. Clinical evaluation should include a careful history of sleep-related symptoms and assessment of the upper airway and lung function. Polysomnography should be considered for those with symptoms suggestive of sleep-disordered breathing. Treatment options depend on the underlying problem, but may include behavioral interventions, weight control, adenotonsillectomy, and nocturnal ventilation.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.021
GPT teacher head0.267
Teacher spread0.246 · 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 designNot applicable
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

Citations214
Published2002
Admission routes1
Has abstractyes

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