Bibliographic record
Abstract
Studies in the research laboratory have demonstrated the complex relationship between fetal and newborn asphyxia and brain damage, a balance between the degree, duration and nature of the asphyxia and the quality of the cardiovascular compensatory response. Clinical studies would support the contention that the human fetus and newborn behave in a similar manner. An accurate diagnosis of asphyxia requires a blood gas and acid base assessment. The clinical classification of fetal asphyxia is based on a measure of metabolic acidosis to confirm that fetal asphyxia has occurred and the expression of neonatal encephalopathy and other organ system complications to express the severity of the asphyxia. The prevalence of fetal asphyxia at delivery is at term, 25 per 1000 live births of whom 15% are moderate or severe; and in the preterm, 73 per 1000 live births of whom 50% are moderate or severe. It remains to be determined how often the asphyxia recognized at delivery may have been present before the onset of labor. There is a growing body of indirect and direct evidence to support the contention that antepartum fetal asphyxia is important in the occurrence of brain damage. Although much of the brain damage observed in the newborn reflects events that occurred before delivery, newborn asphyxia and hypotension, particularly in the preterm newborn, may contribute to the brain damage accounting for deficits in surviving children.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".