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Record W2548642091 · doi:10.3390/w8110499

Environmental Groundwater Vulnerability Assessment in Urban Water Mines (Porto, NW Portugal)

2016· article· en· W2548642091 on OpenAlexaff
María José Afonso, Liliana Freitas, Alcides Pereira, L. J. P. F. Neves, Laura Guimarães, Lúcia Guilhermino, Bernhard Mayer, Fernando Rocha, José M. Marques, Helder I. Chaminé

Bibliographic record

VenueWater · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversity of Calgary
FundersFundação para a Ciência e a TecnologiaUniversidade do Porto
KeywordsHydrogeologyEnvironmental scienceGroundwaterVulnerability assessmentContaminationVulnerability (computing)Water resource managementAquiferHydrology (agriculture)Surface waterSpring (device)Environmental engineeringGeologyEcologyEngineering

Abstract

fetched live from OpenAlex

A multidisciplinary approach was developed to estimate urban groundwater vulnerability to contamination combining hydrogeology, hydrogeochemistry, subterranean hydrogeotechnics, groundwater ecotoxicology and isotope tracers. Paranhos and Salgueiros spring waters in Porto City were used as a case study. Historical and current vulnerability scenarios were compared using hydrogeological GIS-based modelling. Potential contamination sources were mapped around the spring galleries. Most of these were point sources and their potential contamination load was moderate. The ecotoxicological assessment indicated a low acute toxicity potential. Groundwater radionuclides appeared to be mainly controlled by geological factors and biomineralisation. Vulnerability maps suggest that most of the area has a moderate to low vulnerability to contamination. However, some surface sources such as sewage systems cause contamination and contribute to increased vulnerability. This integrated approach was demonstrated to be adequate for a better knowledge of urban hydrogeological processes and their dynamics, and highlighted the importance of a vulnerability assessment in urban areas.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.999

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)0.0290.001

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 head0.199
Teacher spread0.190 · 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; both teacher heads agree on what is shown here.

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

Citations22
Published2016
Admission routes1
Has abstractyes

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