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Endogenous Knowledge of the Attie People on Antischistosomiasis Medicinal Plants in the Adzope Health District, Côte d'Ivoire

2022· article· en· W4311834226 on OpenAlexfundno aff
Ouedje Eppoue Romuald, Koffi Akessé Georges, Tra Bi Boli Francis, Sylla Youssouf, Fah Monh Alice, Moyabi Any Georges Armel, Koukakou Donthy Kouakoubah Richard, Koné Mamidou Witabouna

Bibliographic record

VenueEuropean Scientific Journal ESJ · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsEthnobotanyTraditional medicineMedicinal plantsFabaceaeEuphorbiaceaeBiologyMalariaSchistosomiasisLamiaceaeGeographyMedicineBotanyHelminthsZoology

Abstract

fetched live from OpenAlex

Schistosomiasis or bilharziasis is a parasitic disease caused by flatworms or plathelminthes: bilharzias or schistosomes that live in the venous vascular system. This disease is a major public health problem in countries located in the tropics and subtropics. The general objective of this work was to contribute to the eradication of schistosomiasis in Côte d'Ivoire by highlighting the endogenous knowledge of the Attie people on the medicinal plants used for the treatment of schistosomiasis in the Health District of Adzope. An ethnobotanical survey was conducted among practitioners of traditional medicine (TMP), using a semi-structured interview associated with the show-and-tell technique. A total of 33 medicinal species have been listed. They are divided into 31 genus and 21 botanical families with a predominance of Annonaceae, Asteraceae, Euphorbiaceae and Fabaceae, each with three species. The most cited species are Combretum paniculatum (CF = 14.79%) and Mareya micrantha (CF = 10.56%). The leaves are the most used organs; the decoction is the main mode of preparation of the recipes which are generally administered orally. The results of this study constitute a valuable database for further research in pharmacology and phytochemistry.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.050
GPT teacher head0.233
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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