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Record W2036921790 · doi:10.1177/0883073809342590

Determinants of Ambulation in Children With Spastic Quadriplegic Cerebral Palsy: A Population-Based Study

2009· article· en· W2036921790 on OpenAlexaff
Elisabeth Simard‐Tremblay, Michael Shevell, Lynn Dagenais

Bibliographic record

VenueJournal of Child Neurology · 2009
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineMcGill UniversityMontreal Children's Hospital
Fundersnot available
KeywordsCerebral palsyGross Motor Function Classification SystemMedicineSpasticPediatricsBirth weightPopulationGestational agePhysical therapySpastic cerebral palsyPregnancy

Abstract

fetched live from OpenAlex

The objective of this study was to identify factors that predict ambulation in spastic quadriplegic cerebral palsy. A 4-year registry-based birth cohort was searched for patients with a diagnosis of spastic quadriplegic cerebral palsy. All patients were then divided in 2 groups: (a) Gross Motor Function Classification System level < or = III (ambulant group) and (b) Gross Motor Function Classification System level > or = IV (nonambulant group). Clinical features were then compared between the 2 groups. A total of 85 children with a diagnosis of spastic quadriplegic cerebral palsy were identified. Of these, 65 and 20 were classified in the ''nonambulant'' and ''ambulant'' groups, respectively. The presence of seizures in the first 24 or 72 hours of life and the administration of antibiotics during pregnancy/delivery were all associated with an eventual inability to achieve ambulation. A gestational age < or = 27 weeks, birth weight <1000 g, Caucasian mother, and the presence of hyperbilirubinemia were significantly linked with independent ambulation.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.263
Teacher spread0.253 · 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

Citations17
Published2009
Admission routes1
Has abstractyes

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Same venueJournal of Child NeurologySame topicCerebral Palsy and Movement DisordersFrench-language works237,207