Bibliographic record
Abstract
OBJECTIVE: To outline the journey of a mother of a critically ill child in her quest for care for her infant. This article outlines the barriers faced, disappointments, and the indignity of poverty. Questions and commentary relating to the care of the critically ill in resource-limited environments underline the issues she faces. Critical illness is very common in the developing world with most childhood deaths occurring in Asia and sub-Saharan Africa. These areas are handicapped by limited access to critical care and intensive care facilities. This paper is not intended to review preventive strategies and simple inexpensive treatments that may prevent diseases and diminish critical illnesses. DATA SOURCE: Experience obtained from a sabbatical in Africa. STUDY SELECTION: A literature search with the following terms was conducted: intensive care, critical care, emergency care, children, developing countries, severe pneumonia, ventilator-associated pneumonia, nosocomial infections. DATA EXTRACTION AND SYNTHESIS: Abstracts that seemed to relate to the care of critically ill or injured children from the developing world were then reviewed and relevant aspects were discussed. CONCLUSION: Critical illness is common in areas of the world plagued with minimal resources to deal with its ravages. Parents try to do what is best for their critically ill children, but navigation of systems and lack of resources are daunting propositions. On any given day, this story or versions of it occurs in many parts of Africa and in low income countries in general. I saw similar scenes several times daily in Uganda and Kenya and, although the issues are slightly different in South Africa, failures of healthcare processes resulted in similar adverse outcomes in all areas. This is a mother's story.
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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.011 |
| Insufficient payload (model declined to judge) | 0.009 | 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".