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Record W2167883374 · doi:10.1039/c1em10225g

Arsenic transformations in terrestrial small mammal food chains from contaminated sites in Canada

2011· article· en· W2167883374 on OpenAlexafffundabout
Jared R. Saunders, Christopher Hough, Loren D. Knopper, Iris Koch, Kenneth J. Reimer

Bibliographic record

VenueJournal of Environmental Monitoring · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsRoyal Military College of CanadaDefence Research and Development CanadaStantec (Canada)
FundersNatural Sciences and Engineering Research Council of CanadaMinistère de la Défense Nationale
KeywordsArsenicPhocoenaFood chainEnvironmental chemistryHarbourContaminationWet weightChemistryBiologyEcology

Abstract

fetched live from OpenAlex

Arsenic in terrestrial contaminated sites has the potential to cause harm to residential wildlife. The aim of this study was to determine the arsenic species in wild rodents living in arsenic contaminated habitats, specifically deer mice from Yellowknife, NT and meadow voles from Seal Harbour, NS, along with co-located plants. Methanol : water (1 : 1) extractions were used to optimize the extraction of methylated arsenic(v) species. Total arsenic concentrations were substantially higher in the Yellowknife deer mice (1.7-3.2 µg kg(-1) wet weight in livers) and Seal Harbour meadow voles (0.67-0.97 µg kg(-1) wet weight in livers) living on the contaminated sites with respect to the surrounding background locations (0.12-0.34 µg kg(-1) wet weight in livers). Around 50% of arsenic could be identified in Yellowknife deer mouse tissues, but only <10% was identified in Seal Harbour vole tissues; inorganic arsenic (iii and v) and dimethylarsinic acid were all found. Monomethylarsonic acid was only detected in both the mice and voles living in the contaminated sites. In the Yellowknife food chain, methyl arsenic (v) proportions increased from plants to mouse inner organs, but the trend was not for clear as the Seal Harbour food chain. Seal Harbour voles may be sequestering arsenic in a less mobile form, rather than transforming it.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.869

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 head0.023
GPT teacher head0.186
Teacher spread0.163 · 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 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

Citations17
Published2011
Admission routes3
Has abstractyes

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