Bibliographic record
Abstract
Breastfeeding is the optimal method of infant feeding. Breast milk provides almost all the necessary nutrients, growth factors and immunological components a healthy term infant needs, Other advantages of breastfeeding include reduction of incidences and severity of infections; prevention of allergies; possible enhancement of cognitive development; and prevention of obesity, hypertension and insulin-dependent diabetes mellitus. Health gains for breastfeeding mothers include lactation amenorrhea, early involution of the uterus, enhanced bonding between the mother and the infant, and reduction in incidence of ovarian and breast cancer. From the economic perspective, breastfeeding is less expensive than formula feeding. In most cases, maternal ingestion of medications and maternal infections are not contraindications to breastfeeding. Breastfeeding, however, is contraindicated in infants with galactosemia. The management of common breastfeeding issues, such as breast engorgement, sore nipples, mastitis and insufficient milk, is discussed. Breastfeeding should be initiated as soon after delivery as possible. To promote, protect and support breastfeeding, the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF) developed the Baby-Friendly Hospital Initiative (BFHI) 10 Steps to Successful Breastfeeding. Healthcare professionals have an important role to play in promoting and protecting breastfeeding.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.167 | 0.142 |
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".