Bibliographic record
Abstract
This exploratory research study examined the experience of the Neonatologist with infant death in the Neonatal Intensive Care Unit. Despite recent advances in knowledge and technology infant death continues to occur. The impact these deaths have on the Neonatologist positively or negatively will have implications for the effective care of the infant and family, functioning of the health care team and especially on the Neonatologists themselves. The experience for the Neonatologist has not been widely researched or reported in the literature. This small study has used a review of the pertinent literature, discussion of contributing factors and qualitative research methodology to increase the understanding of the Neonatologists’ experience. Eight Neonatologists from a NICU in Ontario were interviewed using qualitative research methodology. Common themes, similarities and dissimilarities in coping and learning to cope with infant death, implications for educating future Neonatologists and areas for future study were identified. Although the small sample size precluded the drawing of definitive conclusions, the analysis of the data supported findings that were identified in the literature and also introduced some new and unique issues and topics.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".