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Record W1986265624 · doi:10.1207/s15326942dn3101_1

The Impact of Spina Bifida on Development Across the First 3 Years

2007· article· en· W1986265624 on OpenAlexaff
Laura E. Lomax-Bream, Marcia A. Barnes, Kim Copeland, Heather B. Taylor, Susan H. Landry

Bibliographic record

VenueDevelopmental Neuropsychology · 2007
Typearticle
Languageen
FieldMedicine
TopicSpinal Dysraphism and Malformations
Canadian institutionsUniversity of Guelph
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of Health
KeywordsPsychologySpina bifidaCognitionMotor skillDevelopmental psychologyLesionEtiologyCognitive skillLanguage developmentCognitive developmentAudiologyPediatricsNeuroscienceMedicinePsychiatry

Abstract

fetched live from OpenAlex

Early cognitive, motor, and language skills were evaluated in 165 children, 91 with Spina Bifida (SB) and 74 developing typically. Assessments were given at 5 time points (6, 12, 18, 24, and 36 months of age). Three latent growth curve models were conducted to evaluate the development of these early skills, with social economic status and etiology as predictors of growth. Lesion level and shunting effects were included for group comparison. Children with SB exhibited lower levels of functioning in all areas, with slower rates of growth in cognition and language, but more acceleration in growth of motor skills. The impact of lesion level and shunting significantly related to growth in cognition and motor skills but not in language.

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)0.008
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 score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.022
GPT teacher head0.350
Teacher spread0.328 · 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

Citations71
Published2007
Admission routes1
Has abstractyes

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