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Record W3009755201 · doi:10.1371/journal.pone.0229794

Metal oxides and annealed metals as alternatives to metal salts for fixed-ratio metal mixture ecotoxicity tests in soil

2020· article· en· W3009755201 on OpenAlexafffund
Mathieu Renaud, Mark Cousins, Kobby Fred Awuah, Olukayode Jegede, Beverley Hale, José Paulo Sousa, Steven D. Siciliano

Bibliographic record

VenuePLoS ONE · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsUniversity of GuelphUniversity of Saskatchewan
FundersFundação para a Ciência e a TecnologiaNatural Sciences and Engineering Research Council of Canada
KeywordsMetalChemistryLeaching (pedology)Metal toxicityInorganic chemistryEcotoxicitySoil waterEnvironmental chemistryNuclear chemistryToxicity

Abstract

fetched live from OpenAlex

In soil metal ecotoxicology research, dosing is usually performed with metal salts, followed by leaching to remove excess salinity. This process also removes some metals, affecting metal mixture ratios as different metals are removed by leaching at different rates. Consequently, alternative dosing methods must be considered for fixed ratio metal mixture research. In this study three different metal mixture dosing methods (nitrate, oxide and annealed metal dosing) were examined for metal concentrations and toxicity. In the nitrate metal dosing method leaching reduced total metal retention and was affected by soil pH and cation exchange capacity (CEC). Acidic soils 3.22 (pH 3.4, CEC 8 meq/100g) and WTRS (pH 4.6, CEC 16 meq/100g) lost more than 75 and 64% of their total metals to leaching respectively while Elora (6.7 pH, CEC 21 meq/100g) and KUBC (pH 5.6, CEC 28 meq/100g) with higher pH and CEC only lost 13.6% and 12.2% total metals respectively. Metal losses were highest for Ni, Zn and Co (46.0%, 63.7% and 48.4% metal loss respectively) whereas Pb and Cu (5.6% and 20.0% metal loss respectively) were mostly retained, affecting mixture ratios. Comparatively, oxide and annealed metal dosing which do not require leaching had higher total metal concentrations, closer to nominal doses and maintained better mixture ratios (percent of nominal concentrations for the oxide metal dosing were Pb = 109.9%, Cu = 84.6%, Ni = 101.9%, Zn = 82.3% and Co = 97.8% and for the annealed metal dosing were Pb = 81.7%, Cu = 80.3%, Ni = 100.5%, Zn = 89.2% and Co = 101.3%). Relative to their total metal concentrations, nitrate metal dosing (lowest metal concentrations) was the most toxic followed by metal oxides dosing while the annealed dosing method was generally non-toxic. Due to the lack of toxicity of the annealed metals and their higher dosing effort, metal oxides, are the most appropriate of the tested dosing methods, for fixed-ratio metal mixtures studies with soil invertebrates.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.045
GPT teacher head0.259
Teacher spread0.214 · 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 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

Citations8
Published2020
Admission routes2
Has abstractyes

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