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Record W4395675528 · doi:10.1080/17480930.2024.2345033

Modeling the influence of forest vegetation and climate change on the long-term performance of a cover with capillary barrier effects used to control acid mine drainage: the Lorraine case study

2024· article· en· W4395675528 on OpenAlexaffabout
Yves-Dady Botula, Bruno Bussière, Marie Guittonny, Gwendoline Hotton

Bibliographic record

VenueInternational Journal of Mining Reclamation and Environment · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsVegetation (pathology)PhreaticEnvironmental scienceHydrology (agriculture)HydrogeologyDrainageVegetation coverGeologyPhysical geographyGeotechnical engineeringLand useGroundwaterEcologyGeography

Abstract

fetched live from OpenAlex

The Lorraine mine site in Témiscamingue region (Québec, Canada) was reclaimed with a cover with capillary barrier effects (CCBE) to limit acid mine drainage generation. The main objective of this study is to predict the long-term hydrogeological behaviour of the CCBE at Lorraine site, including the influence of vegetation and climate change (CC). Numerical simulations showed that performance of the CCBE is: (1) not affected by forest vegetation and CC in the saturated zone in the north of the Lorraine site and (2) more sensitive to vegetation in the unsaturated zone in the south where the phreatic level is low.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score0.165

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.012
GPT teacher head0.244
Teacher spread0.232 · 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 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

Citations2
Published2024
Admission routes2
Has abstractyes

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