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Record W1965150893 · doi:10.1080/03067310108044383

Approaches to the Determination of Polychlorinated Biphenyl (PCB) Concentrations in Soils / Sediments by Dechlorination to Biphenyl

2001· article· en· W1965150893 on OpenAlexafffund
Qixiang Wu, William D. Marshall

Bibliographic record

VenueInternational Journal of Environmental & Analytical Chemistry · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolychlorinated biphenylChemistryBiphenylSoil waterEnvironmental chemistryExtraction (chemistry)ChromatographyAnalyteSample preparationContaminationMatrix (chemical analysis)HexaneGas chromatographyMagnesiumOrganic chemistryEnvironmental science

Abstract

fetched live from OpenAlex

Abstract A method for the dechlorination of PCB mixtures (Aroclor formulations) to biphenyl was extended to soils. The contaminated sample was mixed with magnesium flakes, potassium hexachloropalladiate (K2PdCl6), propan-2-ol and water then permitted to react for up to six hours. Biphenyl, recovered by extraction into hexane, was quantified by gas chromatography with flame ionization detection. The reaction was very efficient in propan-2-ol / water (∼95%), surfactant emulsion or sand mixture and virtually complete in soil provided that excess magnesium (2 g) and the K2PdCl6 were added to the sample prior to the addition of water. Higher PCB loadings were readily determined in field contaminated soils either by direct determination within the matrix or by standard additions. However, analyte concentrations were appreciably over-estimated in Soxhlet or sonication extracts of a certified reference material that contained sub-ppm levels of analyte. The over-estimation is considered to result from the conversion in part of natural organic matter to biphenyl.

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 score0.209
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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.253
Teacher spread0.229 · 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

Citations4
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Environmental & Analytical ChemistrySame topicToxic Organic Pollutants ImpactFrench-language works237,207