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Record W2778118055 · doi:10.19044/esj.2017.v13n36p192

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

2017· article· en· W2778118055 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Scientific Journal ESJ · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater and Watershed Analysis
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsGroundwater rechargeWatershedHydrology (agriculture)GeologyAquiferGroundwaterDrainageGeography

Abstract

fetched live from OpenAlex

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.

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.

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)0.013
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.431
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.002
Scholarly communication0.0040.001
Open science0.0010.000
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 head0.007
GPT teacher head0.254
Teacher spread0.247 · 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