Management of neonatal jaundice in primary care.
Bibliographic record
Abstract
The Clinical Practice Guidelines on Management of Neonatal Jaundice 2003 was updated by a multidisciplinary development group and approved by the Ministry of Health Malaysia in 2014. A systematic review of 13 clinical questions was conducted using evidence retrieved mainly from Medline and Cochrane databases. Critical appraisal was done using the Critical Appraisal Skills Programme checklist. Recommendations were formulated based on the accepted 103 evidences and tailored to local setting as stated below. Neonatal jaundice (NNJ) is a common condition seen in primary care. Multiple risk factors contribute to severe NNJ, which if untreated can lead to adverse neurological outcomes. Visual assessment, transcutaneous bilirubinometer (TcB) and total serum bilirubin (TSB) are the methods used for the detection of NNJ. Phototherapy remains the mainstay of the treatment. Babies with severe NNJ should be followed-up to detect and manage sequelae. Strategies to prevent severe NNJ include health education, identification of risk factors, proper assessment and early referral.
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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".