Ethnomedicines used in Trinidad and Tobago for urinary problems and diabetes mellitus
Bibliographic record
Abstract
BACKGROUND: This paper is based on ethnobotanical interviews conducted from 1996-2000 in Trinidad and Tobago with thirty male and female respondents. METHODS: A non-experimental validation was conducted on the plants used for urinary problems and diabetes mellitus: This is a preliminary step to establish that the plants used are safe or effective, to help direct clinical trials, and to inform Caribbean physicians of the plants' known properties to avoid counter-prescribing. RESULTS: The following plants are used to treat diabetes: Antigonon leptopus, Bidens alba, Bidens pilosa, Bixa orellana, Bontia daphnoides, Carica papaya, Catharanthus roseus, Cocos nucifera, Gomphrena globosa, Laportea aestuans, Momordica charantia, Morus alba, Phyllanthus urinaria and Spiranthes acaulis. Apium graviolens is used as a heart tonic and for low blood pressure. Bixa orellana, Bontia daphnoides, Cuscuta americana and Gomphrena globosa are used for jaundice. The following plants are used for hypertension: Aloe vera, Annona muricata, Artocarpus altilis, Bixa orellana, Bidens alba, Bidens pilosa, Bonta daphnoides, Carica papaya, Cecropia peltata, Citrus paradisi, Cola nitida, Crescentia cujete, Gomphrena globosa, Hibiscus sabdariffa, Kalanchoe pinnata, Morus alba, Nopalea cochinellifera, Ocimum campechianum, Passiflora quadrangularis, Persea americana and Tamarindus indicus. The plants used for kidney problems are Theobroma cacao, Chamaesyce hirta, Flemingia strobilifera, Peperomia rotundifolia, Petiveria alliacea, Nopalea cochinellifera, Apium graveolens, Cynodon dactylon, Eleusine indica, Gomphrena globosa, Pityrogramma calomelanos and Vetiveria zizanioides. Plants are also used for gall stones and for cooling. CONCLUSION: Chamaesyce hirta, Cissus verticillata, Kalanchoe pinnata, Peperomia spp., Portulaca oleraceae, Scoparia dulcis, and Zea mays have sufficient evidence to support their traditional use for urinary problems, "cooling" and high cholesterol. Eggplant extract as a hypocholesterolemic agent has some support but needs more study. The plants used for hypertension, jaundice and diabetes that may be safe and justify more formal evaluation are Annona squamosa, Aloe vera, Apium graveolens, Bidens alba, Carica papaya, Catharanthus roseus, Cecropia peltata, Citrus paradisi, Hibsicus sabdariffa, Momordica charantia, Morus alba, Persea americana, Phyllanthus urinaria, Tamarindus indicus and Tournefortia hirsutissima. Several of the plants are used for more than one condition and further trials should take this into account.
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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 | 0.000 |
| 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 | 0.001 |
| 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".