Effects of some Biological Covariates on the Probability of First Recurrence of Malaria following Treatment with Artemisinin Combination Therapy
Bibliographic record
Abstract
Many investigations have shown that artemisinin-based combination therapies are effective in the treatment of uncomplicated malaria and that they do not increase parasite resistance to treatment as much as treatment with single substance. We study the relation between some biological covariates and the time to first recurrence of malaria for children treated for malaria in a clinical trial. One group received artesunate plus sulfadoxine-pyrimethamine and the other only sulfadoxine-pyrimethamine. We consider the event malaria-free for the first 42 (and 84) days. We use logistic regression models for the analyses. The main results show that the probability of no recurrence is higher if the parasite density in the blood is high. The results are inconclusive for other explanatory biological variables. The infecting parasites having genes that indicate resistance, gave different results at the two different treatment centres. There was no appreciable difference in the effects of treatment over the two follow-up periods and these treatments do not have any effect on the probability of a recurrence
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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 | 0.013 | 0.061 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".