Review of processes in use to inform the expansion of newborn bloodspot screening programmes
Bibliographic record
Abstract
The National Screening Advisory Committee (NSAC) was established in 2019 as an independent advisory committee to play a strategic role in the development and consideration of population-based screening programmes in Ireland. The role of the NSAC is to provide advice to the Minister for Health and Department of Health on new screening proposals and proposed changes to existing screening programmes. The Health Technology Assessment (HTA) directorate within the Health Information and Quality Authority (HIQA) has been requested by the Department of Health to provide evidence synthesis support to the NSAC under an agreed work programme. \nNewborn bloodspot screening (NBS), or, the 'heel prick test', is completed in the first 72 to 120 hours of life and is provided under the National Newborn Bloodspot Screening Programme (NNBSP). The current programme screens for eight conditions, with a ninth condition under implementation as of June 2021. \nAt the request of the NSAC, HIQA performed a review of international processes in use to inform policy-making on the expansion of NBS programmes. This report was provided to the NSAC to help inform the development of their processes for the assessment of conditions being considered for inclusion in Ireland’s NBS programme.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.262 | 0.372 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".