Neonatal Encephalopathy
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
Background and Objectives: Neonatal encephalopathy (NE) is characterized by an abnormal level of consciousness with or without seizures in the neonatal period. It affects 1-6/1,000 live term newborns. We applied genome sequencing (GS) in term newborns with NE to investigate the underlying genetic causes. Methods: We enrolled term newborns according to inclusion/exclusion criteria during their Neonatal Intensive Care admission. We performed GS trio and applied bioinformatic tools. We developed pipelines for manual filters. We applied in silico prediction tools, protein 3D modeling, and functional characterization to assess the pathogenicity of variants. Results: variants may be causative of NE in our study. Discussion: ) that may cause NE. We believe that protein 3D modeling is an important tool to assess the pathogenicity of CNVs and may advance the discoveries of novel genetic diseases. However, functional characterization of missense variants is essential for discoveries of novel genetic diseases. It seems that GS can help identify more candidate genes compared with ES.
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