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Record W2789780381 · doi:10.1002/dev.21610

Auditory structural connectivity in preterm and healthy term infants during the first postnatal year

2018· article· en· W2789780381 on OpenAlexafffund
Leire Zubiaurre‐Elorza, Annika C. Linke, Charlotte Herzmann, Conor J. Wild, Hester Duffy, David S.C. Lee, Victor K. M. Han, Rhodri Cusack

Bibliographic record

VenueDevelopmental Psychobiology · 2018
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsChildren’s Health Research InstituteWestern University
FundersCanadian Institutes of Health ResearchCanada Excellence Research Chairs, Government of CanadaHealth Research BoardNatural Sciences and Engineering Research Council of CanadaChildren's Health Research Institute
KeywordsMagnetic resonance imagingGestational ageWhite matterFractional anisotropyDiffusion MRIBrainstemTractographyPsychologyAudiologyLanguage developmentAuditory pathwaysMedicinePediatricsDevelopmental psychologyNeurosciencePregnancyBiologyRadiology

Abstract

fetched live from OpenAlex

Assessing language development in the first postnatal year is difficult, as receptive and expressive skills are rudimentary. Although outward manifestations of change are limited, the auditory language system is thought to undergo critical development at this age, as the foundations are laid for the rapid onset of spoken language in the second and third years. We recruited 11 infants, 7 healthy controls (gestational age = 40.69 ± 0.56; range from 40 to 41.43) and preterm babies (gestational age = 28.04 ± 0.95; range from 27.43 to 29.43) who underwent a Magnetic Resonance Imaging study during the first postnatal year (age at scan = 194.18 ± 97.98). We assessed white matter tracts using diffusion-weighted magnetic resonance imaging with probabilistic tractography. Fractional anisotropy was found to be largely mature even at one month, although there was a little further increase during the first postnatal year in both the acoustic radiation and the direct brainstem-Heschl's pathway.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.278

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 head0.029
GPT teacher head0.346
Teacher spread0.317 · 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

Citations8
Published2018
Admission routes2
Has abstractyes

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