Modeling the Geographic Distribution of Prosopis africana (G. and Perr.) Taub. in Niger
Bibliographic record
Abstract
Prosopis africana 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 P. africana 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 P. africana 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 P. africana (128,692.32 km2 in total, 10.16% of the territory). Given the extent of this area revealed by this study, a reforestation policy implementation of P. africana would allow to restore its stands in Niger.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".