Bibliographic record
Abstract
During the transition from fetus to neonate some babies will need active intervention and resuscitation. Neonatal resuscitation and follow up care provided by knowledgeable and skilled health care professionals is critical to a healthy outcome for these babies. Early intervention and prevention of complications is the basic principle in neonatal resuscitation and stabilization. In Saskatchewan there are approximately 12,000 births each year and it is estimated 1300 babies might require intensive care. The ideal way to transport a potentially sick infant is in utero. This involves a consultation with a Perinatal/Neonatal Center to arrange for transfer of the mother. Unfortunately, not all neonatal problems can be recognized to allow transport before birth. The Neonatal Resuscitation Program (NRP) presented in the ”Textbook of Neonatal Resuscitation ” 4th edition, is recommended as the standard for neonatal resuscitation. NRP Instructors throughout Saskatchewan are available to provide this educational program to health care providers caring for newborns. The Post Resuscitation Care of the Sick Newborn (STABLE) and Acute Care of the At-Risk Newborn (ACoRN) education programs are offered to provide additional information on care of the ill newborn. For more information about these programs contact the Perinatal Education
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.053 | 0.017 |
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".