Au-Bi-Te(-Cu) Mineralization in the Wawa Gold Corridor (Ontario, Canada): Implications for the Role of Bi-Rich Polymetallic Melts in Orogenic Au Systems
Bibliographic record
Abstract
The Wawa Gold Corridor, a series of Archean orogenic Au deposits in the Michipicoten greenstone belt, Canada, comprises two styles of Au mineralization: (1) syn-deformation gold associated with pyrite and arsenopyrite; and (2) late- to post-deformation gold associated with chalcopyrite and Bi-Te(-S) phases. Through petrographic and mineral–chemical analysis, it was determined that gold in the latter assemblages precipitated from Bi-rich polymetallic melts during hydrothermal overprinting of the earlier Au-As-S mineralization; this event was likely driven by the emplacement of Archean lamprophyres. The formation and evolution of these melts was governed by fluid–pyrite reaction interfaces, where the bulk composition of the melts was broadly controlled by the trace-element chemistry of the sulphide minerals in the local host rocks. This suggests that the melt-formation event involved mobilization of existing metal endowments related to early Au events, rather than addition of new Au, Bi, and Te. Thus, the deposition of high-grade Au by Bi-rich melts was dependent on pre-existing sulphide mineralization, both as a source of metals and as micro-environments that stabilized the melts. The paragenesis documented in the Wawa Gold Corridor (i.e., early hydrothermal Au-As-S mineralization and late melt-related Au-Bi-Te mineralization) has been previously recognized in numerous other orogenic and non-orogenic Au deposits. Herein, it is suggested that this apparent consistency in the timing of melt events across multiple systems probably reflects the physicochemical conditions (i.e., fO2-aH2S) of orogenic fluids being incompatible with molten Bi. Bi-rich polymetallic melts are hence unlikely to form primary Au mineralization in orogenic systems but can, however, have a significant impact on the ultimate deposit-scale distribution of Au via secondary mobilization and enrichment.
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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 | 0.001 |
| 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".