Sulfide and Fe-Ti-P liquid immiscibility in the Ni-Cu-Co ovoid deposit of the Voisey’s Bay complex, Labrador, Canada
Bibliographic record
Abstract
Abstract In the Voisey’s Bay complex, sulfide-matrix breccias developed through the percolation of dense sulfide melt, leading to the displacement of the silicate melt within partially molten silicate-matrix breccias. In these sulfide matrix-breccias, hydrous silicate rims are commonly present at the interface between the sulfide matrix and the silicate framework. Multiple lines of evidence support a magmatic origin of these hornblende-biotite rims, which was largely coeval with the emplacement of the sulfide melt in the magmatic breccias. The formation of the hornblende-biotite rims required the addition of alkalis and water that could not have entirely been sourced from either the sulfide melt or the silicate framework. Through the integration of compositional maps with major and trace element analyses of the main accessory minerals, we propose that the critical components required for the development of the hydrous silicate rims in sulfide-matrix breccias originated from an immiscible Fe-Ti-P melt. Distinct textural and compositional features of apatite, hercynite, ilmenite and magnetite support the presence of small amounts of Fe-Ti-P melt in the sulfide melt. This Fe-Ti-P melt likely formed through melt immiscibility in the early stages of the development of the Voisey’s Bay complex, and was transported in the magma conduits together with the sulfide melt.
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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 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".