The Use of Pyrite Chemistry to Vector toward Gold Mineralization, an Example from the Drogo Prospect, Nunavut, Canada
Bibliographic record
Abstract
Abstract Anomalous high grade Au mineralization has been found in float material at the Drogo Prospect, Nunavut, Canada. However, traditional exploration methods have thus far been unable to find the bedrock source of the mineralization. Recent studies have shown that pyrite trace element chemistry, as determined using LA-ICP-MS, varies between Au-forming and barren fluids. To test whether this also occurred at the Drogo Prospect, we analyzed pyrite in rock samples, including Au-rich samples, moderate Au grade samples, and barren samples. However, little variation in pyrite trace element chemistry was observed, suggesting that pyrite trace element chemistry may not be an effective exploration tool at the Drogo Prospect. To confirm these observations, cluster analysis was used to determine if natural clustering of the data could highlight which samples were more likely to be Au rich; again, no statistical differences could be found between the samples. In contrast to our working hypothesis, this suggests that pyrite trace element chemistry is not an effective exploration tool to find the bedrock source of the Drogo boulder trend.
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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 | 0.002 | 0.001 |
| 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".