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Record W2884967887 · doi:10.1680/jenge.17.00030

The role of pore-gas dynamics in guiding reclamation practices

2018· article· en· W2884967887 on OpenAlexaff
Kyle O Scale, Ian R Fleming

Bibliographic record

VenueEnvironmental Geotechnics · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsOverburdenLand reclamationLandformEnvironmental scienceMethaneWetlandSoil scienceGeologyPore water pressureBedrockMining engineeringGeotechnical engineeringHydrology (agriculture)GeomorphologyGeographyEcology

Abstract

fetched live from OpenAlex

The storage and transportation of pore gasses in overburden and reclamation soil covers were evaluated using statistical analyses and finite difference numerical modelling to guide mine operators regarding practical issues surrounding the construction of overburden landforms, design of soil cover systems and management of reclamation sites. Factors that were found to impact gas transfer were soil moisture, soil temperature, differential pressures and dry bulk density of the overburden landform. Furthermore, the construction of the overburden landform appears to be more impactful to pore-gas dynamics than the design of the soil covers. Practicable recommendations can therefore be inferred to facilitate simultaneously methane oxidation in the uppermost horizon of the overburden while maintaining sufficient pore-gas oxygen in the plant-rooting zone of the soil covers to facilitate growth and survivability of reclamation vegetation. It is recommended that overburden be placed to approximately 1·6 Mg/m 3 . Mine operators should also recognise and manage extreme moisture conditions in the soil covers and uppermost overburden to mitigate restrictions in gas exchange and methane oxidation.

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 score0.256
Threshold uncertainty score0.644

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.010
GPT teacher head0.233
Teacher spread0.223 · 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
Published2018
Admission routes1
Has abstractyes

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