MétaCan
Menu
Back to cohort

Medicinal Plants Used by the Inhabitants of Alfred Nzo District Municipality in the Eastern Cape Province, South Africa

2019· article· en· W3209907187 on OpenAlexvenueno aff
Zingisa Thinyane, Alfred Maroyi

Bibliographic record

VenueJournal of Pharmacy and Nutrition Sciences · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEthnobotanical and Medicinal Plants Studies
Canadian institutionsnot available
FundersUniversity of Fort HareNational Research Foundation
KeywordsMedicinal plantsTraditional medicineCapeEthnobotanyMalariaMedicineGeography

Abstract

fetched live from OpenAlex

Plant species used as herbal medicines play an important in the provision of primary healthcare in several rural communities. The current study was aimed at documenting medicinal plants used by the inhabitants of Alfred Nzo District Municipality in the Eastern Cape province, South Africa. Information on medicinal plants used for primary healthcare was collected through open-ended interviews with a sample of 124 participants selected via snowball-sampling technique between April 2017 and May 2018. A total of 34 plant species and one fungus species representing 20 families were used in the treatment of 13 different human diseases. The major diseases treated by the documented species included respiratory system, pain, sores and wounds, infections and infestations, digestive system, blood and cardiovascular system, fever and malaria, general ailments, reproductive system and sexual health and mental disorders. Popular herbal medicines with relative frequency citation (RFC) values exceeding 0.50 included Bulbine frutescens, Clivia miniata var. miniata, Elephantorrhiza elephantina, Centella asiatica, Hypoxis hemerocallidea, Dicerothamnus rhinocerotis, Leonotis leonurus, Agapanthus africanus and Datura stramonium. Such repository of medicinal plants and fungi reinforces the need for an evaluation of their biological activities as a basis for developing future medicines and pharmaceutical products.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.145

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0000.000
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 head0.072
GPT teacher head0.306
Teacher spread0.233 · 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

Citations8
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Pharmacy and Nutrition SciencesSame topicEthnobotanical and Medicinal Plants StudiesFrench-language works237,207