Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pain, inflammation, and fever are interconnected defence responses that, when dysregulated, underpin many diseases. The present study evaluated the ameliorative effect of hydromethanolic extract of Dioscorea bulbifera (HEDB) on pain, fever and inflammation using Wistar rat models. Fresh bulbils of D. bulbifera were dried, pulverised and extracted using 80% aqueous methanol. Twenty-five (25) male Wistar rats (200–250 g) were randomly assigned to five groups (n=5) and used for the study. Group I served as the negative control and received distilled water, group II served as the positive control and was treated with a standard drug, while groups III, IV and V were treated with HEDB at 200, 400, and 800 mg/kg, respectively. Analgesic, anti-inflammatory, and antipyretic tests were performed following established protocols. The present study reveals that oral treatment with HEDB significantly elevated pain threshold, with 200 mg/kg significantly greater than that of the standard drug, Felxicam. In the albumin-induced paw oedema model, HEDB treatment significantly reduced paw diameter at the 3-hour time point, exhibiting a 48.81% inhibition of oedema. This was superior to the 35.70% inhibition observed with 1.5 mg/kg Felxicam. Similarly, treatment with HEDB on yeast-induced pyrexia significantly lowered rectal temperature, with peak effect observed at 400 mg/kg (4.88%), which was lower than the effect of the positive control, Paracetamol (5.97%). These findings demonstrate that hydromethanol extracts of Dioscorea bulbifera exhibit potent analgesic and anti-inflammatory activities, alongside mild antipyretic effect. The evidence from this study provides a scientific validation for its traditional use in managing these conditions.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.008 |
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 it