MétaCan
Menu
Back to cohort
Record W2777615850 · doi:10.5539/ijb.v10n1p17

Medicinal Plants Sold as Anti-Haemorrhagic in the Cotonou and Abomey-Calavi Markets (Benin)

2017· article· en· W2777615850 on OpenAlexvenueno aff
Jean Robert Klotoé, Koffi Koudouvo, J-M Ategbo, C. Dandjesso, Victorien Dougnon, Frédéric Loko, M Gbéassor, K. Dramane

Bibliographic record

VenueInternational Journal of Biology · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEthnobotanical and Medicinal Plants Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMaceration (sewage)Traditional medicineMedicinal plantsDecoctionPlant speciesBiologyBiotechnologyGeographyBotanyMedicineEngineering

Abstract

fetched live from OpenAlex

Market herbalists are one of the primary uses of primary health care for people in developing countries. They contribute to the conservation of endogenous plants and knowledge. In order to identify plants with antihemorrhagic properties sold in markets in southern Benin, an ethnopharmacological survey was carried out among 34 herbalists in 17 markets in Cotonou and Abomey-Calavi. The method used is Triplet Purchase of Medicinal Recipes (ATRM). A total of 38 plant species in 24 families were identified. The most represented family is the Rubiaceae (13.16%). The most cited species are Cissampelos mucronata (12.96%), Hybanthus enneaspermus (9.26%) and Cassytha filiformis (8.02%). Considering the plants mentioned in single use, C. mucronata (37.5%), C. filiformis (12.5%) and N. laevis (10%) were the most cited species. The leafy stem (71%) is the most used part. Two methods of preparation are mainly used, maceration (45%) and decoction (55%). The extracts of these plants could be a source of Improved Traditional Medication (AHT) for the treatment of haemorrhages.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.522
Threshold uncertainty score0.146

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.315
Teacher spread0.282 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of BiologySame topicEthnobotanical and Medicinal Plants StudiesFrench-language works237,207