Papaya Leaf Extract Elevates Platelet Levels in Individuals With Dengue Fever
Bibliographic record
Abstract
Dengue, an arboviral illness, is notorious for inducing thrombocytopenia, leading to bleeding and heightened mortality risk. Carica papaya leaf extract has shown efficacy in elevating platelet counts. A 35-year-old male presented with fever, fatigue, and body pain persisting for four days. Additionally, he complained of severe back pain, ocular discomfort, and brief episodes of nosebleeds. Testing revealed a positive NS1 antigen, prompting the initiation of intravenous normal saline, paracetamol, and papaya extract tablets. Despite initial platelet levels of 74,000, a subsequent decline to 30,650 was observed following another nosebleed. Subsequently, the patient's spouse administered freshly prepared papaya leaf extract orally three to four times daily, resulting in a platelet count of 120,320 on day 14. Timely recognition of declining platelet levels and the commencement of C. Papaya leaf extract contributed significantly to averting mortality risks.
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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 | 0.000 | 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) | 0.001 | 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".