Bibliographic record
Abstract
Four new petrogenetic and metallogenic models are proposed herein to explain the formation of important mineral deposits in the Grenville Province, providing a framework from which to reappraise Grenvillian mineral potential. Recognition of a high-pressure metamorphic belt within the Grenville Province suggests a potential for eclogite-hosted rutile deposits, an important and much-sought commodity. A recently developed Norwegian model proposes that anorthosite genesis occurred through lower crust underplating and coeval partial melting, rather than by plume magmatism. Applied to the Grenville Province, the new petrogenetic model may provide insight into the widespread occurrence of platinum group element (PGE) poor nickel showings and the distribution of chromite, Ti-rich, and low-Ti iron-oxide deposits within the Grenville and adjacent terranes. A new type of sedimentaryexhalative (SEDEX) mineralization formed by oxidized brines has been defined following the discovery of new deposits in Australia. Applied to the Grenville Province, it provides a possible explanation for two long-recognized features of marble-hosted zinc deposits: (i) the presence of meta-siderite beds occurring as distal haloes around SEDEX zinc deposits, and (ii) the mutually exclusive division of these SEDEX deposits into massive sulphide and nonsulphide groups. The discovery of the giant Olympic Dam iron-oxide coppergold (IOCG) deposit in Australia renewed the interest in magmatic low-Ti iron-oxide deposits in the Grenville Province that have been known and mined since early colonial times. Subsequent exploration in the northeastern part of the Grenville Province revealed the presence of breccia-hosted CuAuU rare-earth element (REE)-bearing iron-oxide mineralization. This deposit and other low-Ti iron-oxide deposits in the southwestern Grenville Province have a previously undocumented close spatial and temporal association with Ti-rich iron-oxide deposits. These examples demonstrate how new petrogenetic, tectonic, and ore deposit models developed in unmetamorphosed rocks can be successfully adapted to high-grade terranes, where they stimulate mineral exploration in these challenging conditions. Furthermore, by tracking the formation of ore deposits in the lower crust, the existence of unsuspected metallogenic associations in the higher crust, such as the low-Ti and high-Ti iron-oxide association observed in the Grenville Province, may be revealed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".