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Record W2413036640 · doi:10.5539/enrr.v6n2p136

Modeling the Geographic Distribution of Prosopis africana (G. and Perr.) Taub. in Niger

2016· article· en· W2413036640 on OpenAlexvenueno aff
Laouali Abdou, Abdoulaye Diouf, Maman Maârouhi Inoussa, Boubacar Moussa Mamoudou, Salamatou Abdourahamane Illiassou, Ali Mahamane

Bibliographic record

VenueEnvironment and Natural Resources Research · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOverexploitationReforestationGeographyDistribution (mathematics)ForestryEnvironmental protectionEcologyBiologyMathematics

Abstract

fetched live from OpenAlex

<p class="1Body"><em>Prosopis africana </em>is a species of great socio-economic importance, threatened with extinction from its natural habitat in Niger due to overexploitation. The main objective of this study is to determine the potential geographic distribution of <em>P. africana</em> in Niger. Climatic and botanical data has been collected and used to model the distribution, on the basis of principle of maximum entropy (MAXENT) using MAXENT 3.3.3k, DIVA-GIS 7.5, and ArcGIS 10.0. programs. Rainfall and temperature are the most significant variables in the distribution of <em>P. africana</em> in Niger. Thus the southern band of the country (from the sudanian zone to the sahelio-soudanian zone), the wettest, is the area conducive to the development of <em>P.</em> <em>africana </em>(128,692.32 km<sup>2</sup> in total, 10.16% of the territory). Given the extent of this area revealed by this study, a reforestation policy implementation of <em>P. africana</em> would allow to restore its stands in Niger.</p>

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 score0.107
Threshold uncertainty score0.238

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 studies0.0000.001
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 head0.026
GPT teacher head0.241
Teacher spread0.215 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

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