Neonatal Jaundice in Low- and Middle-Income Countries: Lessons and Future Directions from the 2015 Don Ostrow Trieste Yellow Retreat
Bibliographic record
Abstract
Severe neonatal hyperbilirubinemia, defined as total serum bilirubin (TSB) ≥20 mg/dl, is associated with a higher risk of permanent neurological sequelae and death. Jaundice can and should be promptly diagnosed and treated. Reliable methods for TSB assay are not always readily available, particularly in low- and middle-income countries, making the true incidence of severe neonatal jaundice (NNJ) difficult to estimate. To gather a more comprehensive picture, a symposium addressing NNJ worldwide was organized during the 2015 Don Ostrow Trieste Yellow Retreat. Data collected by several researchers in different regions of the world were presented and differences/similarities discussed. This report points out the need for: (1) a coordinated worldwide effort to define the burden and the causes of severe NNJ and its consequences; (2) aggressive educational programs for families and health personnel to facilitate timely care-seeking, and (3) accurate diagnostics and effective phototherapy.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".