MétaCan
Menu
Back to cohort
Record W2039478710 · doi:10.1139/s01-002

Removal of Aroclor 1016 from contaminated soil by Solvent Extraction Soil Agglomeration Process

2002· article· en· W2039478710 on OpenAlexvenueaboutno aff
Abdul Majid, Steve Argue, B.D. Sparks

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicPesticide and Herbicide Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental remediationExtraction (chemistry)LoamSoil waterEconomies of agglomerationEnvironmental chemistryContaminationSlurrySoil contaminationEnvironmental scienceSolventChemistryPulp and paper industryChromatographyEnvironmental engineeringSoil scienceChemical engineeringEcologyOrganic chemistry

Abstract

fetched live from OpenAlex

This communication reports the results of a study to assess the suitability of the National Research Council of Canada's Solvent Extraction Soil Remediation (SESR) process to effectively remediate soils contaminated with PCBs. A series of small-scale batch extraction tests were carried out using a loamy clay soil sample spiked with Aroclor 1016. The variables examined included the effects of solvent type, water addition, agglomerate size, and extraction additives. Aroclor 1016 recovery rates for the SESR process were higher than those found for high shear agitation of soil slurries without agglomeration and Soxhlet extraction (93.9 ± 1.9, 90.6 ± 1.5 and 82.7 ± 0.9% respectively). A two-stage extraction process, with a series of three wash steps incorporated into the solid–liquid separation operation, produced a treated soil with an average Aroclor 1016 concentration of 49 ± 8 mg/kg on a dry weight basis (95.4 ± 2.4% removed). Key words: PCBs, soil remediation, agglomeration, solvent extraction.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score0.999

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.006
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 teacher head, not a consensus.

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

Citations16
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Environmental Engineering and ScienceSame topicPesticide and Herbicide Environmental StudiesFrench-language works237,207