MétaCan
Menu
Back to cohort
Record W2115430362 · doi:10.1139/t04-044

Biodegradation of monoethanolamine in soil monitored by electrical conductivity measurement: an observational approach

2004· article· en· W2115430362 on OpenAlexfundvenueno aff
Ron CK Wong, L. R. Bentley, Anne W. Ndegwa, Angus Chu, Mehran Gharibi, Stuart Lunn

Bibliographic record

VenueCanadian Geotechnical Journal · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiodegradationEnvironmental remediationElectrical resistivity and conductivityEnvironmental scienceSoil scienceEnvironmental chemistryGeotechnical engineeringMaterials scienceMineralogyGeologyChemistryContaminationOrganic chemistryEcology

Abstract

fetched live from OpenAlex

Monoethanolamine (MEA) is commonly used by the natural gas industry to remove acid gases from the natural gas stream. A series of pan test studies was conducted to examine the biodegradability of MEA in soil recovered from a decommissioned sour gas processing plant site. Test results indicate that MEA was successfully biodegraded or transformed into simple compounds under aerobic and anaerobic conditions. The electrical conductivity (EC) of the soil evolved with changing chemical conditions of its by-products during degradation of MEA. Based on experimental observations, five ranges of EC were correlated with five geochemical zones consisting of various concentrations of MEA and its by-products. The five ranges of EC were translated into equivalent in situ EC ranges. Using these in situ EC ranges, an electrical resistivity tomography image was used to create a geochemical interpretation of the subsurface beneath the plant site. The geochemical interpretation can provide useful information for detailed site assessment and remediation design.Key words: electrical conductivity, biodegradation, monoethanolamine, ammonia, acetate, electrical resistivity tomography, site characterization, observational approach.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.837
Threshold uncertainty score0.951

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.077
GPT teacher head0.254
Teacher spread0.177 · 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 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

Citations9
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeophysical and Geoelectrical MethodsFrench-language works237,207