Indicator mineral signature of the Strange Lake rare earth element deposit, Quebec and Newfoundland and Labrador
Bibliographic record
Abstract
The first detailed study of the indicator mineral signature of a major rare earth element (REE) deposit in glaciated terrain was undertaken at the Strange Lake Zr-Y-HREE deposit in northern Quebec and Newfoundland and Labrador, Canada. The heavy mineral (>3.2 SG) and mid-density (3.0-3.2 SG) nonferromagnetic fractions of bedrock samples from the two mineralized zones were examined to determine potential indicator minerals of REE mineralization. Till samples overlying and up to 50 km down-ice of the deposit were examined to determine the abundance of these minerals at varying distances from the deposit. The deposit contains numerous oxide, silicate, phosphate, and carbonate indicator minerals. Some of the minerals observed in both the bedrock and till samples had not been previously reported for the Strange Lake deposit. The most useful indicator minerals were determined to be Zr-silicates (primary elpidite, secondary gittinsite, and many other hydrated Zr±Y±Ca-silicate minerals), pyrochlore, thorite/ thorianite, monazite/rhabdophane, chevkinite, parisite, bastnaesite, kainosite, and allanite. Rare earth element indicator minerals can now be added to the expanding list of indicator minerals that can be used to explore for a broad range of deposit types and commodities, i.e., diamonds, precious metals, base metals, and strategic metals.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".