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Record W2525553436 · doi:10.1680/jgein.16.00022

New insight on geosynthetic clay liner hydration: the key role of subsoils mineralogy

2016· article· en· W2525553436 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGeosynthetics International · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsQueen's University
FundersAustralian Research Council
KeywordsSubsoilGeosynthetic clay linerWater contentClay mineralsBentoniteSoil waterGeotechnical engineeringGeologySoil scienceMineralogyHydraulic conductivity

Abstract

fetched live from OpenAlex

The hydration of a needle-punched, thermally treated and powdered bentonite-based geosynthetic clay liner (GCL) from four different subsoils was studied at optimum moisture content +2% under isothermal conditions. Contrary to the belief that GCL hydration was strongly dependent on the percentage of clay-sized particles present in the subsoils, it was shown in this investigation that this dependency cannot be generalised to all subsoil types as the presence of smectite in the subsoils can substantially impact GCL water uptake. Smectite content of the subsoil has been found to enhance its water retention capacity, and therefore the relative amount of water available in the subsoil for hydration of the GCL was strongly dependent on the amount of smectite available in the subsoil (i.e., GCL water absorption from smectite-rich soils is impeded). The hydration process from subsoils dominated by smectite mineralogy was governed by the vapour phase, whereas when the smectite content was very low or nil the hydration process involved both vapour and liquid phases if the subgrade was at a water content close to optimum.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score0.999

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.008
GPT teacher head0.214
Teacher spread0.206 · 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