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Record W2892719363 · doi:10.3390/w10101320

Long Term Hydrodynamic Effects in a Semi-Arid Mediterranean Multilayer Aquifer: Campo de Cartagena in South-Eastern Spain

2018· article· en· W2892719363 on OpenAlexaff
Juan Domingo-Pinillos, Javier Senent‐Aparicio, J. L. García-Aróstegui, Paul Baudron

Bibliographic record

VenueWater · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsAquiferGroundwater rechargeAridGeologyHydrology (agriculture)Mediterranean climateGroundwaterWater balanceStructural basinGroundwater flowEnvironmental scienceWater resource managementGeomorphologyGeographyPaleontologyGeotechnical engineeringArchaeology

Abstract

fetched live from OpenAlex

The Mediterranean basin contains many semi-arid environments where aquifers are subject to intensive exploitation, generally to meet irrigation demands. The Campo de Cartagena aquifer is a clear example from such a semi-arid environment, and its hydrodynamic effects have aroused great scientific interest. The main objective of this study is to evaluate the hydrodynamic effects that have occurred in the last century of anthropogenic activity in this aquifer system. This aquifer is subject to intensive exploitation and shows clear deficits in times of drought, with recharge by irrigation playing an important role. This study’s methodology includes groundwater modelling to reconstruct the transient evolution of the aquifer system during the last century, to generate water balances and to illustrate how the evolution of irrigation has, in many ways, changed the aquifer’s groundwater flow pattern. The results delineate the hydraulic communication of the aquifer stratums through specific geological structures, as well as the flow transfer from the Quaternary layer to the Mar Menor and the Mediterranean Sea. The reconstruction of the entire system’s temporal evolution shows a fragile water balance that is supported by surface-water contributions.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.009
GPT teacher head0.224
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.

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

Citations26
Published2018
Admission routes1
Has abstractyes

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