Ebola Laboratory Response at the Eternal Love Winning Africa Campus, Monrovia, Liberia, 2014–2015
Bibliographic record
Abstract
West Africa experienced the first epidemic of Ebola virus infection, with by far the greatest number of cases in Guinea, Sierra Leone, and Liberia. The unprecedented epidemic triggered an unparalleled response, including the deployment of multiple Ebola treatment units and mobile/field diagnostic laboratories. The National Institute of Allergy and Infectious Diseases and the Centers for Disease Control and Prevention deployed a joint laboratory to Monrovia, Liberia, in August 2014 to support the newly founded Ebola treatment unit at the Eternal Love Winning Africa (ELWA) campus. The laboratory operated initially out of a tent structure but quickly moved into a fixed-wall building owing to severe weather conditions, the need for increased security, and the high sample volume. Until May 2015, when the laboratory closed, the site handled close to 6000 clinical specimens for Ebola virus diagnosis and supported the medical staff in case patient management. Laboratory operation and safety, as well as Ebola virus diagnostic assays, are described and discussed; in addition, lessons learned for future deployments are reviewed.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".