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Record W2070043811 · doi:10.1017/s001216220000058x

Body composition in nutritionally adequate ambulatory and non-ambulatory children with cerebral palsy and a healthy reference group

2000· article· en· W2070043811 on OpenAlexaff
K E. Chad, Heather McKay, Gordon A. Zello, D. A. Bailey, Robert A. Faulkner, R. E. Snyder

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2000
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCerebral palsyMedicineFemoral neckBone mineralAmbulatoryFemurSpasticPopulationBone densityPhysical therapyInternal medicineSurgeryOsteoporosis

Abstract

fetched live from OpenAlex

Bone-mineral content (BMC; g) and density (BMD; g/cm2) were measured by dual energy X-ray absorptiometry in the proximal femur, femoral neck, and total body of nutritionally adequate children (n=17; 11 girls, six boys; aged 7.6 to 13.8 years) with spastic cerebral palsy (CP). Bone-mineral-free lean tissue (BMFL; g) and fat mass (FM; g) were obtained from total body scans. Chronological and developmental age-based z scores for the children with CP were derived from a pediatric database (n=894). Children with CP had BMC z scores from -1.8 (total body) to -3.2 (femoral neck) SDs below the normative sample. Non-independent ambulators had lower z scores for total body BMD, femoral neck BMD, and BMC than independent ambulators. The BMFL z score of individuals with CP was 2 SDs below that of the reference group and higher in the independent ambulators than in the non-independent ambulators, whereas FM deviated little. These findings suggest that non-nutritional factors, such as ambulation, account for the low BMC, BMD, and BMFL tissue observed in this population.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.232
Teacher spread0.223 · 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 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

Citations60
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueDevelopmental Medicine & Child NeurologySame topicCerebral Palsy and Movement DisordersFrench-language works237,207