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Record W4388906150 · doi:10.1007/978-3-031-34447-3_17

Application of Foams as a Remediation and Blocking Agent

2023· book-chapter· en· W4388906150 on OpenAlexaff
Olivier Atteia, Henri Bertin, Nicolas Fatin‐Rouge, Emily Fitzhenry, Richard Martel, Clément Portois, Thomas Robert, Alexandre Vicard

Bibliographic record

VenueEnvironmental contamination remediation and management · 2023
Typebook-chapter
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsPorous mediumPulmonary surfactantMaterials scienceEnvironmental remediationRheologyFoaming agentPorosityBlocking (statistics)Chemical engineeringComposite materialEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract Foam consists of a mixture of water loaded with surfactant and gas. Injected into the porous medium, foam has many useful properties for soil remediation. The properties of surfactants facilitate the mobilization of pollutants, and the presence of gas greatly reduces the consumption of reagents but also makes it possible to block the passage of water. The foam rheology also leads to specific effects such as the stabilization of the front. This chapter first describes the characteristics of the foam in air and then in the porous medium. Subsequently, a review of the literature on the experiments carried out in the laboratory makes it possible to highlight all the effects of the foam. The following section is devoted to rare foam injection experiments carried out in a real environment. Finally, a section is devoted to the modeling of foam displacement in a porous medium.

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 score0.002
Threshold uncertainty score0.007

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 head0.005
GPT teacher head0.190
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 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

Citations3
Published2023
Admission routes1
Has abstractyes

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