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Record W2960163516 · doi:10.1680/jenes.18.00042

Numerical modelling of leachate transport into water bodies at a landfill site

2019· article· en· W2960163516 on OpenAlexvenueno aff
B Naveen, J. Sumalatha, R. K. Malik

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLeachateEnvironmental scienceAquiferGroundwaterLand reclamationLeaching (pedology)Bioreactor landfillEnvironmental engineeringContaminationWater qualityWaste managementMunicipal solid wasteGroundwater pollutionHydrology (agriculture)GeologySoil scienceGeotechnical engineeringSoil waterEcologyEngineering

Abstract

fetched live from OpenAlex

This study was carried out to assess the possibility of reclamation of a closed landfill site located at Mavallipura near Bangalore, India. The existing liner system at this site had not completely prevented leachate migration to the underlying aquifers, which required management and control to avoid adverse impact on the surrounding environment. Batch leaching tests and column tests were conducted to estimate the migration rates of different contaminants through soil. The transport rates thus obtained were used as input to the fluidyn-Pollusol model to assess the leachate migration from the landfill. This model may be useful in analysing leachate migration from the landfill and its associated environmental impacts, particularly on groundwater wells and surface water ponds downstream of the site. The results indicated that landfill leachate leakage had a significant effect on the quality of surrounding water bodies.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.172
Teacher spread0.166 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations3
Published2019
Admission routes1
Has abstractyes

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