The spectrum of brain malformations and disruptions in twins
Bibliographic record
Abstract
Twins have an increased risk for congenital malformations and disruptions, including defects in brain morphogenesis. We analyzed data on brain imaging, zygosity, sex, and fetal demise in 56 proband twins and 7 less affected co-twins with abnormal brain imaging and compared them to population-based data and to a literature series. We separated our series into malformations of cortical development (MCD, N = 39), cerebellar malformations without MCD (N = 13), and brain disruptions (N = 11). The MCD group included 37/39 (95%) with polymicrogyria (PMG), 8/39 (21%) with pia-ependymal clefts (schizencephaly), and 15/39 (38%) with periventricular nodular heterotopia (PNH) including 2 with PNH but not PMG. Cerebellar malformations were found in 19 individuals including 13 with a cerebellar malformation only and another 6 with cerebellar malformation and MCD. The pattern varied from diffuse cerebellar hypoplasia to classic Dandy-Walker malformation. Brain disruptions were seen in 11 individuals with hydranencephaly, porencephaly, or white matter loss without cysts. Our series included an expected statistically significant excess of monozygotic (MZ) twin pairs (22/41 MZ, 54%) compared to population data (482/1448 MZ, 33.3%; p = .0110), and an unexpected statistically significant excess of dizygotic (DZ) twins (19/41, 46%) compared to the literature cohort (1/46 DZ, 2%; p < .0001. Recurrent association with twin-twin transfusion syndrome, intrauterine growth retardation, and other prenatal factors support disruption of vascular perfusion as the most likely unifying cause.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".