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Record W4225141646 · doi:10.1080/17480930.2022.2069915

Numerical analysis of cover systems for mining waste in tropical regions

2022· article· en· W4225141646 on OpenAlexaff
Deborah Perotti, Gilson de Farias Neves Gitirana, Thiago Augusto Mendes, M. D. Fredlund

Bibliographic record

VenueInternational Journal of Mining Reclamation and Environment · 2022
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsBentley (Canada)
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsSoil waterEnvironmental scienceMacroporeDrainageCompactionPrecipitationHydrology (agriculture)Land coverTropicsSoil compactionCover cropSoil scienceGeologyGeotechnical engineeringLand useAgroforestryGeographyMeteorologyEngineering

Abstract

fetched live from OpenAlex

The flow of water in mining waste may cause serious environmental impacts associated with acid-rock drainage. In relatively dry climates, dry soil covers have been considered as feasible alternatives to minimise such effects. The objective of this paper is to evaluate the influence of the hydrological cycle and soil type on the performance of dry cover systems, considering the tropical conditions found in Brazil’s central-west region. Numerical analyzes of four different cover systems composed of tropical soils were performed using the Finite Element Method. Among the proposed arrangements, three use a soil that presents a bimodal soil-water characteristic curve and the fourth system employs a unimodal soil. The thicknesses of intermediate materials were varied and different representative precipitation parameters were considered for a period of one year. The results obtained were compared in terms of the internal flow and the capacity of the cover to store water. The results indicate that bimodal soils may not be ideal materials and require specific compaction conditions to reduce the volume of macropores. Unimodal tropical soils presented adequate response as store-and-release materials. The use of an intermediate layer acting as a capillary barrier did not offer significant improvement to the cover systems evaluated.

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 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 score0.213

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)0.0000.000

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 head0.014
GPT teacher head0.221
Teacher spread0.207 · 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.

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

Citations6
Published2022
Admission routes1
Has abstractyes

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