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Record W2092914214 · doi:10.1080/15320383.2012.649375

Influence of Short-Chain Aliphatic Acids on the Phenanthrene Desorption and Mobilization from Contaminated Soil

2012· article· en· W2092914214 on OpenAlexaff
Chunjiang An, Guohe Huang, Hui Yu, Jia Wei

Bibliographic record

VenueSoil and Sediment Contamination An International Journal · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsPhenanthreneChemistryDesorptionOxalic acidCitric acidOrganic acidTartaric acidMalic acidAcetic acidInorganic chemistryEnvironmental chemistryOrganic chemistryAdsorption

Abstract

fetched live from OpenAlex

This study was performed to investigate the influence of short-chain aliphatic acids (SCAAs) on the desorption of phenanthrene from artificially contaminated soils with this polycyclic aromatic hydrocarbon. Five SCAAs examined, including acetic acid, oxalic acid, malic acid, tartaric acid and citric acid, were related to the increase of phenanthrene desorption from two kinds of soil. Citric acid and oxalic acid enhanced phenanthrene desorption to a more significant extent than other organic acids. The effects of pH, SCAA concentration, and ionic strength were further evaluated. The phenanthrene desorption was enhanced as the pH increased. An increase in desorbed phenanthrene from pH 3 to pH 8 was observed, but that was followed by a slight decrease above pH 8 for most SCAAs. The phenanthrene desorption performance showed increments with increasing organic acid concentrations. However, the increase of phenanthrene desorption became less remarkable when SCAA concentrations were above 100 mmol/L. Moreover the results suggested that high ionic strength hindered the desorption of phenanthrene in the presence of SCAAs.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.239
Teacher spread0.227 · 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

Citations4
Published2012
Admission routes1
Has abstractyes

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