Leveraging neonatal neuroimaging for neuroprognostication in presumed hypoxic-ischemic encephalopathy: A framework for clinicians
Bibliographic record
Abstract
Brain magnetic resonance imaging (MRI) in neonates with presumed hypoxic-ischemic encephalopathy (HIE) offers a unique window into the extent and timing of injury, providing valuable insights for neuroprognostication. Brain MRI refines the prediction of functional outcomes, crucial for guiding family counseling and early interventions. The present article focuses on the role of post-rewarming brain MRI in this context, exploring specific MRI findings associated with diverse neurodevelopmental outcomes and highlights the potential of neuroimaging to improve the understanding and prediction of long-term functional outcomes. Utilizing a framework with likelihood categories, this work aims to enhance the accuracy of prediction of adverse outcomes within specific developmental domains, thereby refining neuroprognostication for informed discussions with caregivers.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".