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Record W4292466503 · doi:10.5539/jas.v14n9p86

Morphological Characterization and Diversity of Bambara Groundnuts in Uganda

2022· article· en· W4292466503 on OpenAlexvenueno aff
M. Kiryowa, G. Ddamulira, G. Alenoma, G. Karwani, M. O. Ifeyinwa, O. P. Umeugochukwu, M. Alanyo

Bibliographic record

VenueJournal of Agricultural Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural pest management studies
Canadian institutionsnot available
Fundersnot available
KeywordsCluster (spacecraft)BiologyPrincipal component analysisRandomized block designYield (engineering)Genetic diversityHorticultureAgronomyMathematicsStatisticsDemographyPopulation

Abstract

fetched live from OpenAlex

Sixty nine Bambara groundnut accessions were evaluated at the National Crops Resources Research Institute (NaCRRI), Namulonge, Uganda to determine their morphological variability in a randomized complete block design with three replications. Analysis of variance showed significant (P < 0.01) divergence among accessions for all traits. Cluster analysis exhibited six distinct clusters with the highest intra-cluster distance (8.09) observed in cluster II and the lowest distance (0.00) in cluster VI. Maximum inter-cluster distance was observed between cluster VI and IV and minimum distance between cluster II and IV. Inter-cluster distance was much higher than intra-cluster distance suggesting a wider variability among accessions. All late maturing accessions with high yield were grouped in cluster V while early maturing accessions were grouped in cluster III. Results of principal component analysis indicated that both yield and vegetative traits were the principal discriminatory characteristics. The accessions evaluated exhibited high diversity for most traits indicating that they can be used in breeding programs to develop varieties with desirable traits.

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 score0.808
Threshold uncertainty score0.524

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.019
GPT teacher head0.202
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.

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
Published2022
Admission routes1
Has abstractyes

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