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Record W2730816295 · doi:10.20286/jeas.v3i1.17

Effect of Farming Activities on Tree Diversity, Density and Community Structure in Agoi-Ekpo, Cross River State Nigeria

2016· article· en· W2730816295 on OpenAlexvenueno aff
A.I. Iwara, T.N. Deekor, GN Njar

Bibliographic record

VenueNova Journal of Engineering and Applied Sciences · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsShrubBasal areaVegetation (pathology)Species richnessSpecies diversityForestryPlant communityEcologyBiologyAgroforestryGeography

Abstract

fetched live from OpenAlex

Tree/shrub species richness, tree/shrub density, basal cover, community structure and distributional pattern were evaluated and compared in fallows of 10yr-old and 5yr-old in Agoi-Ekpo, Cross River State. Vegetation data were collected from 20 randomly selected plots (10 plots for each fallow community) of 0.04 ha. A total of 16 tree/shrub species belonging to 12 families were enumerated in the 20 plots. Vegetation structure (crown cover, basal cover, girth and ground cover) differed significantly between the vegetation fallows (P = 0.01). Tree/shrub density differed significantly (t = 13.620, P = 0.01) between the fallow communities with mean values of 168 and 131 trees/shrubs recorded per plot in the 10yr-old and 5yr-old fallows respectively. Simpson’s index of diversity revealed that vegetation in the 10yr-old fallow was more diverse and heterogeneous (0.89) than the vegetation in the 5yr-old fallow (0.86). The difference in vegetation characteristics was attributed to the nature of previous site disturbance and the years of fallow

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score0.268

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 head0.018
GPT teacher head0.226
Teacher spread0.209 · 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
Published2016
Admission routes1
Has abstractyes

Explore more

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