White Micas as a tool for tracking pegmatite evolution and its use in Li exploration. A case study of Wekusko Lake, Manitoba, Canada.
Bibliographic record
Abstract
The Wekusko Lake pegmatite field is part of the Green Bay Group of pegmatites located near Snow Lake, Manitoba, Canada. Within this field, there are at least 13 spodumene-bearing pegmatites of varying degrees of mineralization. The abundance of white micas and the chemical affinity to incorporate Li and other trace elements into its crystalline structure makes white micas an ideal indicator mineral. The evolution of a melt can be tracked using trace elements in white mica. The K/Rb ratio vs Cs is used to determine a link between increasing evolution and increased Li contents of both the white mica and the pegmatite. White mica compositions were examined using portable Raman and LIBS to evaluate whether Li contents can be determined in the field. The LIBS was able to identify the pegmatites dikes with the highest Li contents, which can be applied to real-time decision-making during exploration.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".