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Record W2898411098 · doi:10.20546/ijcmas.2018.710.372

Deterioration of Natural Forests by Dislpacements at Al Genaina Locality, Al Genaina State, Sudan

2018· article· en· W2898411098 on OpenAlexaboutno aff
Ismail Mohamed Fangama, Fatah Al Rahaman Bakheet

Bibliographic record

VenueInternational Journal of Current Microbiology and Applied Sciences · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsClearanceHectareForestryNatural (archaeology)GeographyQuarter (Canadian coin)AgroforestrySowingLocalityEnvironmental scienceAgricultureArchaeologyAgronomyBiology

Abstract

fetched live from OpenAlex

The research was carried out at the internally displacement persons camps around Al Genaina Locality. Its objectives are to assess the status of natural forests so as to know the density of trees, their types and distribution in the study area. The activities of displacements in the area caused the deterioration of natural forests. Point-Centered Quarter Method (PCQ) was used to calculate the trees density. The results showed that the tree density was five trees per hectare. Clotropis procera became the dominant species in the study area due to continuous cutting down of tees. The study concluded that the trees were completely degraded in research area. The study recommended that, planting cleared area and protecting remaining trees in displacements areas.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.521
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.020
GPT teacher head0.283
Teacher spread0.263 · 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 designBench or experimental
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

Citations0
Published2018
Admission routes1
Has abstractyes

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