Re: Guidelines for detection, management and prevention of hyperbilirubinemia in term and late preterm newborn infants (35 or more weeks' gestation) – Summary. Paediatr Child Health 2007;12(5):401–7
Bibliographic record
Abstract
To the Editor, I would like to comment on the Canadian Paediatric Society statement on the guidelines for jaundice published in the May/June issue of Paediatrics & Child Health. On at least two occasions the statement mentions breastfeeding being a risk factor for hyperbilirubinemia. This is an unfortunate way of putting it, is very misleading and inaccurate, as well as reinforces the prejudices of many health professionals with regard to breastfeeding. Early-onset hyperbilirubinemia is not due to breastfeeding or breastmilk, but to the lack of breastmilk. The study by Bertini et al (1), not referenced in the statement, backs up our clinic's extensive clinical experience of what is really happening and what the real issue is. Support for breastfeeding in most Canadian hospitals is so poor that many babies are not breastfeeding well until the milk ‘comes in’ and are, in fact, only pretending to breastfeed. There is not a large volume of colostrum available in the first few days, but there is enough, if the baby gets it. Because of poor intake of breastmilk, one cannot say that they are breastfeeding, which leads directly to hyperbilirubinemia due to an increased enterohepatic circulation of bilirubin. I appreciate the paragraph on supporting breastfeeding and it is well stated. But unfortunately, individuals experienced in helping mothers breastfeed well are not always easy to come by and paediatricians rarely figure among them. What is necessary is an upgrading of breastfeeding knowledge and skills of the nursing staff and physicians (particularly paediatricians) who deal with newborn babies
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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.008 | 0.002 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.013 | 0.024 |
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".