MétaCan
Menu
Back to cohort
Record W4391814809 · doi:10.1080/09297049.2024.2307662

Assessing the impact of infantile hydrocephalus on visuomotor integration through behavioural and neuroimaging studies

2024· article· en· W4391814809 on OpenAlexafffund
Derya Adil, Emma G. Duerden, Roy Eagleson, Sandrine de Ribaupierre

Bibliographic record

VenueChild Neuropsychology · 2024
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsWestern University
FundersAcademic Medical Organization of Southwestern Ontario
KeywordsPsychologyHydrocephalusPrecuneusNeuroimagingFunctional neuroimagingNeuroscienceCorticospinal tractAudiologyDiffusion MRIFunctional magnetic resonance imagingMedicineMagnetic resonance imagingPsychiatry

Abstract

fetched live from OpenAlex

Infantile hydrocephalus considerably impacts neurodevelopment, warranting attention to potential long-term consequences on visuomotor functions. The current study investigated the impact of infantile hydrocephalus on functional connectivity within the posterior cortex. Fourteen patients, who were treated for infantile hydrocephalus, were matched for age and sex with 14 typically-developing controls. Both groups had a mean age of 9 years old. Resting-state functional MRI was used to conduct a functional connectivity analysis within the visuomotor integration network, including the inferior frontal occipital fasciculus, superior longitudinal fasciculus, and frontal aslant tract. Patients had reduced functional connectivity in visuomotor pathways compared to typically-developing children with notable impact on the left and right fusiform gyrus and precuneus. Children with infantile hydrocephalus also performed significantly lower in tasks involving visuomotor integration, visual processing, visuospatial skills, motor coordination, and fine motor manipulation. This study enhances our understanding of the multifaceted impact of infantile hydrocephalus on both neural connectivity and considering behavioral outcomes.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.893
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

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

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 head0.140
GPT teacher head0.496
Teacher spread0.357 · 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 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

Citations6
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueChild NeuropsychologySame topicAdvanced Neuroimaging Techniques and ApplicationsFrench-language works237,207