Epigenomic newborn screening for conditions with intellectual disability and autistic features in Australian newborns
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
This study describes a protocol to assess a novel workflow called Epi-Genomic Newborn Screening (EpiGNs) on 100,000 infants from the state of Victoria, Australia. The workflow uses a first-tier screening approach called methylation-specific quantitative melt analysis (MS-QMA), followed by second and third tier testing including targeted methylation and copy number variation analyzes with droplet digital PCR, EpiTYPER system and low-coverage whole genome sequencing. EpiGNs utilizes only two 3.2 mm newborn blood spot punches to screen for genetic conditions, including fragile X syndrome, Prader-Willi syndrome, Angelman syndrome, Dup15q syndrome and sex chromosome aneuploidies. The program aims to: identify clinically actionable methylation screening thresholds for the first-tier screen and estimate prevalence for the conditions screened.
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