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Record W2026648916 · doi:10.1039/b304716d

Estimates of total polychlorinated biphenyl (PCB) compounds in soils/sediments by hydrogenolysis to dicyclohexyl

2003· article· en· W2026648916 on OpenAlexafffund
Sadia Ehsan, Shiv O. Prasher, William D. Marshall

Bibliographic record

VenueJournal of Environmental Monitoring · 2003
Typearticle
Languageen
FieldEngineering
TopicEnvironmental remediation with nanomaterials
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHydrogenolysisEnvironmental chemistryChemistryPolychlorinated biphenylBiphenylHexaneSedimentSoil waterCatalysisEnvironmental scienceOrganic chemistryGeologySoil science

Abstract

fetched live from OpenAlex

A method to determine the total PCB content by hydrogenolysis (hydrodechlorination and hydrogenation) of chlorinated biphenyl compounds was extended to natural particulate matrices (soil and sediment). The contaminated soil was suspended in hexane in the presence of Pd/gamma-Al2O3 in a hydrogen atmosphere then permitted to react for one hour at 65 degrees C. Dicyclohexyl, recovered in the hexane, was quantified by gas chromatography mass spectrometry. The reaction was very efficient for soil/sediment in hexane suspension and virtually complete provided that excess catalyst was added to samples that were burdened with higher PCB loadings prior to reaction otherwise some partial hydrogenation of biphenyl was also observed. The proposed method was validated with the analysis of five certified reference materials.

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 categoriesMeta-epidemiology (narrow)
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 score0.091
Threshold uncertainty score1.000

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 science0.0000.000
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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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

Citations10
Published2003
Admission routes2
Has abstractyes

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