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Record W3011870063 · doi:10.5539/jps.v9n1p59

An Evaluation of the Potentials of Moringa oleifera Lam), A Vegetable and Hedgerow Plant for Diet Supplements and Multipurpose Utilizations

2020· article· en· W3011870063 on OpenAlexvenueno aff
Adeleke Salami, C. Nwadike

Bibliographic record

VenueJournal of Plant Studies · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMoringa oleifera research and applications
Canadian institutionsnot available
Fundersnot available
KeywordsMoringaCivil servantsLocal government areaTraditional medicineGeographyAgricultural scienceSocioeconomicsToxicologyLocal governmentBiologyMedicineSociologyPolitical science

Abstract

fetched live from OpenAlex

A survey was carried out to evaluate the potentials of Moringa oleifera (Lam) within and outside the Kano metropolis of Kano state, Nigeria, where it serves as vegetable and hedgerow plant for diet supplements and multipurpose utilizations. Structured interview was used with a total of 100 respondents, randomly spread. In the Kano metropolis, which falls within the Kano city, 4 Local Government Areas (LGAs) were covered. These are: Nassarawa, Ungogo, Tarauni and Dala; while Madobi, Minjiibir, Garun Mallam and Dambatta LGAs were covered outside the Kano metropolis. Results of the structured interview using the Convenience Sampling Technique revealed that Moringa is very rich nutritionally, economically and medicinally. Moringa utilization cuts across various categories of people with 69% usage recorded for male and 40% for literate users, while students and civil servants had 21% each. Moringa farmers that cultivates simultaneously on farmlands and backyard gardens were however 73%. Analysis of results further indicated that the plant is rated very high as diet supplements in the state, owing to the fact that it is very rich nutritionally, apart from its economic and medicinal values. It is however recommended that its nursery propagation be encouraged, and community interest in its cultivation mobilized.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.131

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 head0.204
GPT teacher head0.355
Teacher spread0.150 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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