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Record W4283313905 · doi:10.1016/j.jconhyd.2022.104047

Characterizing the hydraulic and transport properties of a constructed coarse tailings sand aquifer

2022· article· en· W4283313905 on OpenAlexafffund
Owen F. Sutton, Eric Kessel, Behrad Gharedaghloo, Jonathan S. Price

Bibliographic record

VenueJournal of Contaminant Hydrology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTailingsOil sandsHydraulic conductivityAquiferGeologyTRACERGroundwaterPermeability (electromagnetism)Soil sciencePermeameterDeposition (geology)SiltLand reclamationGeotechnical engineeringEnvironmental scienceHydrology (agriculture)AsphaltGeomorphologySoil waterSediment

Abstract

fetched live from OpenAlex

Millions of tonnes of coarse tailings sand are produced every year as a byproduct of the bitumen extraction process in the Athabasca Oil Sands Region. These tailings materials contain residual quantities of mobile solutes, which can be transported through groundwater to downgradient terrestrial and aquatic ecosystems. The anticipated ubiquity of coarse tailings sand on the post-mined landscape necessitates the characterization of its hydraulic and transport properties. Hydraulic conductivity and dispersivity was evaluated at multiple scales, and included the first field-scale tracer test conducted in a tailings sand aquifer. Average hydraulic conductivity derived using laboratory cores, single-well response tests, and the tracer test were 3.2 m d−1, 2.9 m d−1, and 3.4 m d−1, respectively. These measurements demonstrated close agreement and were consistent with expectations of a material that experiences some grain-size segregation and homogenization due to the oil sands process and the nature of deposition. The field-scale tracer test appeared to obtain the asymptotic dispersivity of the coarse tailings sand aquifer, reaching a maximum value of 0.5 m after 18 m of displacement. Coarse tailings in the oil sands that experience similar processes of segregation, settling, and deposition on the reclamation landscape could be expected to have similar hydraulic properties.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score0.286

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 science0.0000.000
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 head0.010
GPT teacher head0.194
Teacher spread0.184 · 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 designBench or experimental
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

Citations7
Published2022
Admission routes2
Has abstractyes

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