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Record W4200084159 · doi:10.1201/9781003078777-22

Use of GCLs to control migration of hydrocarbons in severe environmental conditions

2021· book-chapter· en· W4200084159 on OpenAlexaffabout
H.M. Li, Richard J. Bathurst, R. Kerry Rowe

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsRoyal Military College of CanadaQueen's University
Fundersnot available
KeywordsEnvironmental science

Abstract

fetched live from OpenAlex

Over a period of 40 years, fuels spills and leaks have occurred at Canadian sub-Arctic and Arctic Distant Early Warning Line (DEW Line) sites. The Canadian Department of National Defence has initiated cleanup program of these sites estimated to cost $320 million (Cdn). Access to these sites is often limited and the environmental conditions are severe. This paper describes the construction of an experimental subsurface composite geosynthetic barrier wall installed in the summer of 2001 to limit migration of hydrocarbons at one of these sites prior to excavation and ex-situ cleanup. The selection of the barrier system, design considerations, site conditions and practical lessons learned from the construction of a barrier system in a permafrost region are described. An in-situ monitoring system was also installed to assess the performance of the barrier system.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.013
GPT teacher head0.196
Teacher spread0.183 · 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 source (direct Gemma or distilled Codex), 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
Published2021
Admission routes2
Has abstractyes

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Same topicMicrobial bioremediation and biosurfactantsFrench-language works237,207