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Record W2100404612 · doi:10.2136/vzj2014.02.0013

Accuracy of Lysimeters for Dissolved Copper, Antimony, Lead, and Zinc Sampling under Small Arms Backstop

2014· article· en· W2100404612 on OpenAlexafffund
Richard Martel, Pascal Castellazzi, Luc Trépanier, Mathieu Laporte‐Saumure, Sylvie Brochu

Bibliographic record

VenueVadose Zone Journal · 2014
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsDefence Research and Development CanadaInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLysimeterSorptionZincPorosityCopperEnvironmental scienceEnvironmental chemistryChemistryMaterials scienceSoil waterMetallurgySoil science

Abstract

fetched live from OpenAlex

Three assays were conducted to evaluate the reliability of lysimeters in detecting concentrations of Cu, Pb, Sb, and Zn in interstitial water of the vadose zone. Two box lysimeters (BLs) made from polyvinyl chloride (PVC) and polyvinylidene fluoride (PVDF) and three tension lysimeters (TLs) of different types were used. Assays were conducted with two concentrations of dissolved metals, undiluted and diluted in a 1:10 ratio, and at three different pHs. The assays were made to evaluate the sorption induced by the lysimeter material itself, by standard quartz sand added to the BLs, and by two types of glass beads placed around the porous cup of the TLs. Generally, BLs were more suitable for interstitial water sampling than TLs. Among the TLs, the one made of nylon was more reliable than the two others. Box lysimeters are a good choice to obtain accurate and comparable results for Cu, Pb, Sb, and Zn analysis. However, they have to be backfilled with natural soil found at the exact location of the lysimeter and not with standard quartz sand. Nylon TLs can also be used for water sampling for Sb, Pb, and Zn analysis but not for Cu. Glass beads may interact with dissolved metals and their use around the suction cup in TLs can be avoided by using the fine fraction of natural sediments (<125 μm) found at the location of the porous cup. Water samples from TLs do not need to be filtered for dissolved metal analysis because they are already filtered by the porous cup.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.193
Threshold uncertainty score0.919

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.064
GPT teacher head0.319
Teacher spread0.255 · 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 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

Citations2
Published2014
Admission routes2
Has abstractyes

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