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Record W2023929628 · doi:10.1155/2014/167971

Leaching of Chromium, Copper, and Arsenic from CCA-Treated Utility Poles

2014· article· en· W2023929628 on OpenAlexafffund
Cynthia A. Coles, Joseph Abraham Arisi, Marion E. Organ, Geoff Veinott

Bibliographic record

VenueApplied and Environmental Soil Science · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsFisheries and Oceans CanadaNalcor Energy (Canada)Memorial University of Newfoundland
FundersMemorial University of Newfoundland
KeywordsLeaching (pedology)ChromiumSoil waterChromated copper arsenateArsenicCopperEnvironmental chemistryTotal organic carbonEnvironmental scienceRainwater harvestingOrganic matterCation-exchange capacityMetalChemistrySoil science

Abstract

fetched live from OpenAlex

Concentrations of Cu, Cr, and As in soils surrounding 26 Douglas Fir Chromated Copper Arsenate (CCA) treated utility poles and in rainwater runoff from a new CCA treated utility pole segment (log) suspended outside in a cylinder were studied. The age of the utility poles, distances from the poles, rainfall amounts, and characteristics of soil samples including cation exchange capacity (CEC), pH, and total organic carbon (TOC) were considered. Heavier rainfall, damp conditions, and more weathered poles contributed to the greatest leaching of Cu, Cr, and As. The maximum measured soil concentrations of Cu, Cr, and As were 37.5, 65.5, and 38.9 mmol/kg and maximum Cu, Cr, and As concentrations in rainwater run-off were 14, 77.7 and 55.8 μ mol/L. Metal concentrations decreased with distance from the poles and, except at one utility pole location, Cu was the most leached of the three elements. The As appeared to have greater mobility in the soil than the Cr. Along the transmission line nearest the coast and from which the greatest amount of samples was collected, soil CEC and TOC values were the highest and the CEC and TOC were directly and strongly correlated.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.177
Teacher spread0.173 · 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 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

Citations25
Published2014
Admission routes2
Has abstractyes

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