Management and outcome of extremely low birth weight infants
Bibliographic record
Abstract
Survival of extremely low birth weight (ELBW) and extremely premature (EP) infants has shown consistent improvement thanks to advances and innovations in perinatal and neonatal care. Regionalization, with high-risk deliveries in a tertiary perinatal center, offers the coordinated, collaborative, expert and specialized care needed by these mothers and their infants. Despite decreasing rates of the major neonatal morbidities observed in recent years, these continue still to be significant for ELBW/EP infants, impacting their overall prognosis. After NICU discharge and in the first years of life, issues with health, growth and development are common. In school age and adolescence, problems with behavior, socialization and cognition are prevalent. Adult outcomes of ELBW/EP need further clarity, emphasizing the importance for consistent long-term follow-up for this special cohort. Proceedings of the 10th International Workshop on Neonatology · Cagliari (Italy) · October 22nd-25th, 2014 · The last ten years, the next ten years in Neonatology Guest Editors: Vassilios Fanos, Michele Mussap, Gavino Faa, Apostolos Papageorgiou
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".