A case of an avoidable admission to an Ebola treatment unit with malaria and an associated heat illness: Table 1
Bibliographic record
Abstract
We present a 27-year old British nurse admitted to the Kerry Town Ebola Treatment Unit, Sierra Leone, with symptoms fitting suspect-Ebola virus disease (EVD) case criteria. A diagnosis of Plasmodium falciparum malaria and heat illness was ultimately made, both of which could have been prevented through employing simple measures not utilised in this case. The dual pathology of her presentation was atypical for either disease meaning EVD could not be immediately excluded. She remained isolated in the red zone until 72 h from symptom onset. This case highlights why force protection measures are important to reduce the incidence of both malaria and heat illness in deployed military and civilian populations. These prevention measures are particularly pertinent during the current EVD epidemic where presenting with these pathologies requires clinical assessment in the 'red zone' of an Ebola treatment unit.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".