A review of rare-element (Li-Cs-Ta) pegmatite exploration techniques for the Superior Province, Canada and large worldwide tantalum deposits; Exploration and Mining Geology
Bibliographic record
Abstract
Abstract — Rare-element pegmatites may host several economic commodities, such as tantalum (Ta-oxide minerals), tin (cassiterite), lithium (ceramic-grade spodumene and petalite), and cesium (pollucite). Key geological features that are common to pegmatites in the Superior province of Ontario and Manitoba, Canada, and in other large tantalum deposits worldwide, can be used in exploration. An exploration project for rare-element pegmatites should begin with an examination of a regional geology map. Rare-element pegmatites occur along large regional-scale faults in greenschist and amphibolite facies metamorphic terranes. They are typically hosted by mafic metavolcanic or metasedimentary rocks, and are located near peraluminous granite plutons (A/CNK> 1.0). Once a peraluminous granite pluton has been identified, then the next step is to determine if the pluton is barren or fertile. Fertile granites have elevated rare element contents, Mg/Li ratio < 10, and Nb/Ta ratio < 8. They commonly contain blocky K-feldspar and green muscovite. Key fractionation indicators can be plotted on a map of the fertile granite pluton to determine the fractionation direction: presence of tourmaline, beryl, and ferrocolumbite; Mn content in garnet; Rb content in bulk K-feldspar; and Mg/Li and Nb/Ta ratios in bulk granite samples. Pegmatite dikes with the most economic potential for Li-Cs-Ta deposits occur the greatest distance (up to 10 km) from the parent granite.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".