More accuracy estimation of the worm burden in the ascariasis of children in Kinshasa
Bibliographic record
Abstract
ABSTRACT The present study aims to give a better estimate of the worm burden (ascariasis) to address accurately the impact of intestinal parasitosis on the children growth in Africa. The study was conducted on 20 subjects aged 10 months to 10 years (Mean ± SD: 5.6 ± 2.3 years). They were treated with 10 mg/kg of Pyrantel pamoate. The next day, the stools were collected, washed and filtered to harvest all adult ascaris. In total, 141 ascaris (71 males and 70 females) were extracted for 879.9 g of stool. The geometric mean of eggs counted was 29 by 2 mg of stool. The daily eggs laying per female was estimated to 202,500 eggs/days (CI95%: 128,800 – 276,200). Statistical analysis shows that the parasitic worm burden was proportional both to the number eggs counted per unit of stool volume, and to age of infested subject. A regression model based on these two parameters, with a coefficient of determination equal to 59 %, was retained. Thus, for an old subject respectively of 1, 5 and 10 years, at which 1 egg of ascaris in approximately 2 mg of a preparation would lodge a respective parasitic mass of 1, 3 and 9 g. The results are in the form of confidence interval. For example, for a 5 years old subject with an average of 10 eggs (CI95% = 5.6 - 14.4) after reading of 2 separated preparations coming from the same specimen, the estimated parasitic load is laying between 7 and 11 g.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".