Environmental Geochemistry of Kimberlite Materials: Diavik Diamonds Project, Lac de Gras, Northwest Territories, Canada
Bibliographic record
Abstract
Abstract — Prior to the development of the Diavik Diamonds Project, baseline studies were con-ducted to determine the geochemical characteristics of four kimberlite orebodies as an aid in the design of both the water-management system and the facilities for containment of processed kim-berlite and ore stockpiles. Materials tested included field samples of volcaniclastic and pyroclastic kimberlite, processed kimberlite (i.e., kimberlite ore which had been screened and washed as part of the processing procedure), and sedimentary mudstone (a minor xenolithic unit which was assimi-lated during kimberlite emplacement). Approximately 200 samples of kimberlite materials were col-lected as part of the geochemistry program. Test-work included whole-rock chemical analyses, acid-base accounting, kinetic leach tests using columns, and mineralogical analyses. Diavik kimberlite has major oxide and trace-element concentrations consistent with global aver-ages for kimberlite. The mean total-sulfur content of the kimberlite material is 0.22 wt % S, but with a significant range. The kimberlite has an excess of carbonate minerals over sulfide minerals (aver-age CO2 = 4 wt%, present mainly as calcite), and has a mean neutralization potential of 311 kg CaCO3 equivalent/tonne. A reactive form of framboidal pyrite associated specifically with the mud-stone xenoliths is the primary source of sulfide-sulfur. Long-term kinetic tests confirmed the pre-
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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".