Volumetric Analysis of Hearing-Related Structures of Brain in Children with GJB2-Related Congenital Deafness
Bibliographic record
Abstract
Background: Children with non-syndromic hereditary sensorineural hearing loss (SNHL) provide an opportunity to explore the impact of hearing on brain development. Objective: This study investigates volumetric differences of key hearing-related structures in children with gap junction protein beta 2 GJB2-related SNHL compared to controls. Materials and methods: Ninety-four children with SNHL (n = 15) or normal hearing (n = 79) were studied using automated volumetric segmentation. Heschl’s gyrus (HG), anterior HG (aHG), planum temporale (PT), medial geniculate nucleus (MGN), and nucleus accumbens (NA) were analyzed relative to total brain volume (TBV) at two different age groups: (1) 7−12 months and (2) 13 months−18 years. Two-sided t-tests were used to evaluate differences between groups. Differences were considered significant if p < 0.007. Results: Significantly smaller aHG-to-TBV ratios were found in 13-month-to-18-year-old patients (p < 0.0055). HG-, PT-, MGN-, and NA-to-TBV ratios were smaller in the same age group, without reaching a significant level. Conversely, HG- and NA-to-TBV were larger in the younger age group. No significant differences were found between the groups for age and TBV. Conclusions: In this exploratory volumetric analysis of key hearing-related structures, we observed age-related changes in volume in children with GJB2-related SNHL.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".