The 2014 Ebola Virus Outbreak in West Africa: Current Perspectives for Prevention and Treatment
Bibliographic record
Abstract
In 2014, West Africa has been the scene of the worst Ebola virus outbreak in history, with no end in sight [1-4]. This health crisis is reportedly associated with an outlier strain of Zaire Ebola virus [4]. While the first infections were reported in December of last year, the number of cases has literally exploded during the summer months of 2014, affecting mainly Guinea, Liberia and Sierra Leone, with a few cases in Mali, Nigeria and Senegal. According to the World Health Organization (WHO), as many as 13703 people have been infected by the Ebola virus as of October 27, resulting in 4922 fatalities [5]. The real figures are most likely higher as the healthcare systems in these countries have been overwhelmed by the large number of cases, the limited resources and the lack of basic facilities. While the local Ebola outbreaks in Senegal and Nigeria were declared over in October, the transmission remained persistent and widespread in Guinea, Liberia, and Sierra Leone, especially in the capital cities of these countries. Notably, on a smaller scale, there has also been in 2014 a separate and independent outbreak of Ebola virus in the Democratic Republic of the Congo, which involved 66 cases and resulted in 49 deaths so far, although the situation there seems to remain under relative control [5].
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".