Characterization of arsenic and antimony minerals in Yellowknife Bay sediments
Bibliographic record
Abstract
Yellowknife Bay, Northwest Territories, Canada, is a waterbody valued by surrounding communities for its subsistence, recreational, and cultural use. Located adjacent to the former Giant and Con Mines, Yellowknife Bay has received inputs from mine waste streams enriched in arsenic (As), antimony (Sb), and metals since the late 1930s. Lake sediments in Yellowknife Bay provided a record of metal(loid) contamination from aerially deposited roaster stack emissions, mine effluent, and direct disposal of Giant Mine tailings. A sediment sampling program was conducted in Yellowknife Bay to characterize both As and Sb mineralogy by scanning electron microscopy-mineral liberation analysis (SEM-MLA). Results from nine sediment cores collected in summer (August 2018, July 2019) and winter (March 2019) confirmed that As was mobile relative to layers of enrichment associated with peak mining emissions both downwards, where it precipitated as authigenic sulfides (interpreted to be realgar), and upwards where it was attenuated by Fe-oxyhydroxides and possibly roaster-generated Fe-oxides near the sediment water interface. Antimony minerals appeared to be stable in Yellowknife Bay sediments with no distinct evidence of post-depositional mobility identified. The observed prevalence of arsenic trioxide (As2O3) in near surface sediments proximal to Giant Mine suggested that As and Sb contamination is ongoing, likely from terrestrial weathering of contaminated soils and shoreline outcrops. Arsenic bearing oxide minerals were prevalent in near-surface sediments and may become unstable should redox conditions in the hypolimnion change; prolonged anoxia would destabilize the As phases and release As to bottom waters. Therefore, continual monitoring of hypolimnion conditions in Yellowknife Bay is necessary.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".