Sources and circulation of water and arsenic in the Giant Mine, Yellowknife, NWT, Canada
Bibliographic record
Abstract
Recovery of gold from arsenopyrite-hosted ore in the Giant Mine camp, Yellowknife, NWT, Canada, has left a legacy of arsenic contamination that poses challenges for mine closure planning. Seepage from underground chambers storing some 237,000 tonnes of arsenic trioxide dust, has As concentrations exceeding 4000 ppm. Other potential sources and sinks of As also exist. Sources and movement of water and arsenic are traced using the isotopes of water and sulphate. Mine waters (16 ppm As; AsV/AsIII approximately 150) are a mixture of two principal water sources--locally recharged, low As groundwaters (0.5 ppm As) and Great Slave Lake (GSL; 0.004 ppm As) water, formerly used in ore processing and discharged to the northwest tailings impoundment (NWTP). Mass balance with delta18O shows that recirculation of NWTP water to the underground through faults and unsealed drillholes contributes about 60% of the mine water. Sulphate serves to trace direct infiltration to the As2O3 chambers. Sulphate in local, low As groundwaters (0.3-0.6 ppm As; delta34SSO4 approximately 4% and delta18OSO4 approximately -10%) originates from low-temperature aqueous oxidation of sulphide-rich waste rock. The high As waters gain a component of 18O-enriched sulphate derived from roaster gases (delta18OSO4) = + 3.5%), consistent with their arsenic source from the As2O3 chambers. High arsenic in NWTP water (approximately 8 ppm As; delta18OSO4 = -2%) derived from mine water, is attenuated to close to 1 ppm during infiltration back to the underground, probably by oxidation and sorption by ferrihydrite.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".