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Exploration of Plant Species Used by Bapedi Ethnic Group for Ethnoveterinary Purposes: A Case Study of Ga-Mphahlele Region in the Limpopo Province, South Africa

2019· article· en· W4212906504 on OpenAlexvenueno aff
Sebua Silas Semenya, Sekgothe Mokgoatšana, 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
KeywordsFodderGeographyFlora (microbiology)Traditional medicineEthnobotanyMedicinal plantsAgroforestryBiologyBotanyMedicine

Abstract

fetched live from OpenAlex

The use of plant resources by the Bapedi people in the Limpopo province in South Africa is regarded as part of their tradition and culture. This study was aimed at documenting ethnoveterinary uses of plants in Ga-Mphahlele region in the Limpopo province, South Africa. Information was gathered through semi-structured questionnaires supplemented by field observations from 30 randomly selected Pedi speaking people in Ga-Mphahlele region of the Limpopo province. A total of 52 plant species from 32 plant families were used for 18 ethnoveterinary purposes. The majority of the species (21.2%) were used as fodder, followed by ethnoveterinary medicinal applications against wounds (19.2%), diarrhoea (17.3%), ticks (13.5%) and worms (11.5%) in domestic animals such as cattle, chickens, dogs, donkeys, doves, goats and sheep. The species with frequency of citation (RFC) higher than 0.70 included Citrullus lanatus (fodder), Vachellia karroo (ethnoveterinary medicine and fodder), Sclerocarya birrea subsp. caffra (fodder), Aloe ferox (ethnoveterinary medicine), Drimia sanguinea (ethnoveterinary medicine), Sarcostemma viminale subsp. viminale (ethnoveterinary medicine) and Sorghum bicolor (fodder). The traditional knowledge about forage and ethnoveterinary medicines demonstrated by the Bapedi people enable extension officers and policy makers to appreciate how local communities perceive and utilize plant resources around them.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score0.116

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.242
GPT teacher head0.351
Teacher spread0.109 · 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 designQualitative
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

Citations4
Published2019
Admission routes1
Has abstractyes

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