Identification Des Zones Potentielles De Recharge Des Aquifères Fracturés Du Bassin Versant Du N’zo (Ouest De La Côte d’Ivoire) : Contribution Du SIG Et De La Télédétection
Bibliographic record
Abstract
In a watershed one of the most important data is recharge because it is the main groundwater supply. Recharge is however, a difficult parameter to calculate due to its variability. The objective of this study is to propose a method of identifying potential recharge zone which is applicable to large watersheds. The study area is the N’zo watershed located in the West of Côte d’Ivoire. It covers an area of 4,300 km2 . The water supply of the population is essentially ensured by the fractured aquifers which are the regional aquifers.The data used in this study are classified in two groups1) the cartographic data are composed of geological soil and drainage maps; and 2) data from remote sensing which consist of slope, land use and fractures maps. These data are combined through a multi-criteria analysis to facilitate spatial analysis and identification of potential recharge areas. The results indicate that potential areas of high recharge account for about 20% of the total watershed area. They are mainly located in the south and center and appear fragmented in the north of the watershed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".