MétaCan
Menu
Back to cohort
Record W2020175215 · doi:10.1080/10934529.2011.539115

An experimental study on the bio-surfactant-assisted remediation of crude oil and salt contaminated soils

2011· article· en· W2020175215 on OpenAlexaff
Zhang Wen, Jianbing Li, Guohe Huang, Weikun Song, Yuefei Huang

Bibliographic record

VenueJournal of Environmental Science and Health Part A · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsRhamnolipidEnvironmental remediationSoil contaminationPulmonary surfactantTotal petroleum hydrocarbonChemistryContaminationEnvironmental chemistrySoil waterSalt (chemistry)BioremediationHydrocarbonPetroleumEnvironmental scienceSoil scienceOrganic chemistryGeology

Abstract

fetched live from OpenAlex

The effect of bio-surfactant (rhamnolipid) on the remediation of crude oil and salt contaminated soil was investigated in this study. The experimental results indicated that there was a distinct decline of total petroleum hydrocarbon (TPH) concentration within the soil when using rhamnolipid during a remediation period of 30 days, with maximum TPH reduction of 86.97%. The most effective remediation that was observed was with rhamnolipid at a concentration of 2 CMC in soil solution, and a first-order TPH degradation rate constant of 0.0866 d(-1). The results also illustrated that salts in soil had a negative impact on TPH reduction, and the degradation rate was negatively correlated with NaCl concentration in soil solution. The analysis of soil TPH fractions indicated that there was a significant reduction of C13-C30 during the remediation process when using bio-surfactant.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.297
Teacher spread0.242 · 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

Citations21
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Environmental Science and Health Part ASame topicMicrobial bioremediation and biosurfactantsFrench-language works237,207