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Record W910769997

Rational Selection of Surfactant in Surfactant-Based Remediation

2001· article· en· W910769997 on OpenAlexaboutno aff
Robort D. Cody

Bibliographic record

VenueEconomic and Environmental Geology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsnot available
Fundersnot available
KeywordsPulmonary surfactantChromatographyChemistryTolueneSurface tensionSolubilityCentrifugationShakerChemical engineeringOrganic chemistry
DOInot available

Abstract

fetched live from OpenAlex

Sutfactants may be used in remediation of subsoil and aquifer contaminated with hydrophobic compounds. The objectives of this study were to select potentially suitable sUlfactants that solubilize toluene present as a contaminant and to determine the effectiveness of toluene removal from Ottawa sand by the selected surfactants. Material used as the model soil was Ottawa sand and the organic used as model contaminant was toluene. Used experimental methods were separatory funnel experiment and shaker table agitation/centrifugation experiments. Based on the experimental results, the following conclusions were drawn; t) In the surfactant selection, six different surfactants were chosen based on surfactant types, toxicity, and water solubility. These six were focused into two on the basis of HLB and surface tension study, separatory funnel experiment, shaker table and centrifugation experiments. The two most suitable surfactants were Sandopan JA36 (an anionic surfactant), and Pluronic L44 (a non-ionic surfactant). 2) In the shaker table agitation and centrifugation experiments, the highest recovery of the toluene was 96% which was obtained with one surfactant wash plus two water rinses using an anionic surfactant (Sandopan JA36).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.998

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.182
Teacher spread0.176 · 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.

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

Citations0
Published2001
Admission routes1
Has abstractyes

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