Arsenic transformations in terrestrial small mammal food chains from contaminated sites in Canada
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".