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Record W1915330453 · doi:10.3148/65.3.2004.124

<i>Energy Requirements of Children</i>With Cerebral Palsy

2004· review· en· W1915330453 on OpenAlexaffvenue
Sophie Hogan

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2004
Typereview
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsAcadia University
Fundersnot available
KeywordsCerebral palsyResting energy expenditurePopulationMedicineEnergy expenditureWastingDiseasePhysical medicine and rehabilitationPhysical therapyPediatricsEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Energy requirements of children and adolescents with cerebral palsy appear to be disease-specific and different from the current recommendations for healthy children, varying depending upon functional capacity, degree of mobility, severity of disease, and level of altered metabolism. Feeding problems are prevalent in many of these children, and can result in inadequate energy intake. Wasting of voluntary muscles, a common symptom of cerebral palsy, contributes to reduced resting energy needs; nevertheless, the location of the central nervous system lesion may also influence energy requirements. To guarantee individualized, accurate, and optimal energy recommendations for this population, resting energy expenditure should preferentially be measured by indirect calorimetry. Equations and formulae to predict healthy people's resting energy expenditure are available, but tend to overestimate these children's energy needs. Future studies should address the role of the central nervous system in regulating energy metabolism in this population. When adequately nourished, children and adolescents with cerebral palsy appear more tranquil and require decreased feeding time, which gives caregivers time to develop the child's functional independence and character. Understanding energy requirements of this population will provide caregivers and health professionals with guidelines for providing optimal nutritional status.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.974
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.097
GPT teacher head0.403
Teacher spread0.306 · 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

Citations32
Published2004
Admission routes2
Has abstractyes

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