Cerebrospinal Fluid and Parenchymal Brain Development and Growth in the Healthy Fetus
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to apply quantitative magnetic resonance imaging to characterize absolute cerebrospinal fluid (CSF) development, as well as its relative development to fetal brain parenchyma in the healthy human fetus. DESIGN: We created three-dimensional high-resolution reconstructions of the developing brain for healthy fetuses between 18 and 40 weeks' gestation, segmented the parenchymal and CSF spaces, and calculated the volumes for the lateral, third, and fourth ventricles; extra-axial CSF space; and the cerebrum, cerebellum, and brainstem. From these data, we constructed normograms of the resulting volumes according to gestational age and described the relative development of CSF to fetal brain parenchyma. RESULTS: Each CSF space demonstrated major increases in volumetric growth during the second half of gestation: third ventricle (23-fold), extra-axial CSF (11-fold), fourth ventricle (8-fold), and lateral ventricle (2-fold). Total CSF volume was related to total brain volume (p < 0.01), as was lateral ventricle to cerebral volume (p < 0.01); however, the fourth ventricle was not related to cerebellar or brainstem volume (p = 0.18-0.19). RELEVANCE: Abnormalities of the CSF spaces are the most common anomalies of neurologic development detected on fetal screening using neurosonography. Normative values of absolute CSF volume, as well as relative growth in comparison to intracranial parenchyma, provide valuable insight into normal fetal neurodevelopment. These data may provide important biomarkers of early deviations from normal growth, better distinguish between benign variants and early disease, and serve as reference standards for postnatal growth and development in the premature infant.
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.
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 | 0.000 |
| 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 it