The First Golden Minutes of the Extremely-Low-Gestational-Age Neonate: A Gentle Approach
Bibliographic record
Abstract
An increasing body of evidence has revealed that interventions performed during resuscitation of extremely-low-gestational-age neonates (ELGANs) may have a direct influence on the immediate survival and also on long-term morbidity. It has been proposed that interventions in the delivery room and/or hypothermia could trigger changes constitutive of chronic lung disease. New approaches in the first minutes of life using more gentle parameters of intervention are being studied. Thus, titrating inspiratory fraction of oxygen, the use of non-invasive ventilation to reduce trauma to the lung, the use of polyethylene/polyurethane wrapping to avoid hypothermia and delaying cord clamping altogether constitute promising initiatives. The first minutes of life are a valuable window for intervention. However, whilst these practice changes make sense and there are emerging data to support them, further evidence including long-term follow up is needed to definitively change resuscitation procedures in ELGANs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".