Métallogénie du tantale: application aux différents styles de minéralisations en tantale dans la pegmatite de Tanco, Manitoba, Canada
Bibliographic record
Abstract
Tantalum is a high-tech metal that is mainly mined from rare-element pegmatites. Although tantalum mineralogy has been well characterized, very little is known about the processes that control the formation of Ta deposits. The goal of my thesis is to constrain Ta mineralization processes in the giant Tanco pegmatite (Canada), the third most important Ta deposit in the world. The Tanco pegmatite is extremely complex in terms of petrogenesis and mineralogy, and tantalum mineralization shows a complexity that reflects the highly fractionated features of the igneous body. I investigated two different aspects of Ta mineralization in the Tanco pegmatite: 1) its association with metagabbro rafts embedded in the pegmatite; 2) its association with late mica alteration of the central zones of the pegmatite. The fundamental questions behind those studies are : is Ta mineralization influenced by external factors ? What is the role of aqueous fluids (originating either externally or internally from the pegmatite) on Ta mineralization ? Through the study of these two complementary styles of mineralization, I was able to evaluate the contribution of magmatic versus metasomatic processes in the Ta mineralization, and to advance a metallogenetic model for Ta mineralization at Tanco, whereby Ta enrichment is considered as entirely magmatic in origin.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".