Pediatric Oncology Hospice: A Comprehensive Review
Bibliographic record
Abstract
Pediatric hospice is a new terminology in current medical literature. Implementation of pediatric hospice care in oncology setting is a vast but subspecialized field of research and practice. However, it is accompanied by substantial uncertainties, shortages and unexplored sections. The lack of globally established definitions, principles, and guidelines in this field has adversely impacted the quality of end-of-life experiences for children with hospice needs worldwide. To address this gap, we conducted a comprehensive review of scientific literature, extracting and compiling the available but sparse data on pediatric oncology hospice from the PubMed database. Our systematic approach led to development of a well-organized structure introducing the foundational elements, highlighting complications, and uncovering hidden gaps in this critical area. This structured framework comprises nine major categories including general ideology, population specifications, role of parents and family, psychosocial issues, financial complications, service locations, involved specialties, regulations, and quality improvement. This platform can serve as a valuable resource in establishing a scientifically reliable foundation for future experiments and practices in pediatric oncology hospice.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".