Abstracts – Geological Association of Canada, Newfoundland Section – 2011 Spring Technical Meeting
Bibliographic record
Abstract
This paper describes the application of surficial geochemistry in the search for rare-earth elements and rare metals (REE/ RM).Examples of the responses to known occurrences, as well as some untested anomalies, are described, as well as some of the issues in analysis, and interpretation of the results thereof.The regional-scale provincial lake-sediment and water database comprises multielement analyses for samples from 16,657 sites in the island of Newfoundland and 18,648 sites in Labrador.In addition, samples of lake sediment and water have been collected at 6,600 sites in more than 20 focused, detailed studies in Labrador, and this database continues to be expanded.Till coverage in Labrador has also been selective, with 2,610 samples collected from five detailed surveys, although the coverage of the island has been more systematic, with 7% currently covered, at a density of about 1.6 per km2.There are numerous REE/RM anomalies in both Newfoundland and Labrador.Of the eight known occurrences or districts in Labrador, six have an expression in either lake sediments or tills, or both.The Misery Lake occurrence in Quebec, located close to the border with Labrador, also has a strong geochemical and geophysical expression.In Newfoundland, only one of three known occurrences or districts is spatially associated with such a feature.Some anomalies are present on a regional scale: for example, the Flowers River Complex and Letitia Lake regions, and the glacial dispersion train from the Strange Lake deposit.Others are more restricted in extent, indicating that detailed examination of the regional geochemical databases is necessary; in some cases information in the assessment files may also prove useful, since it may have been acquired in the search for other metals with the REE/RM potential overlooked.The behaviour of certain rare metals is strongly controlled by the relative amounts of clastic and chemically-precipitated material in lake sediment, and by high background content of certain rock types.These environmental factors may give rise to false anomalies or in some cases the masking of the response to mineralization.The apparent extent of anomalies in till may also be interrupted by variations in the type of glacial sediment that is available for sampling.The track record of various Canadian geochemical labs in performing REE/RM analyses is variable, but some are capable of delivering high-quality analyses for all of the rare earths and rare metals, at all concentration levels.It may not be advisable to apply a blanket single method for all of these elements and the potential for inter-element interferences, in particular, should not be underestimated.It is also highly recommended that detailed examination be made of QAQC data, both external and internal, before making any recommendations based on the results. Midland's new rare-earth element (REE) discoveries at Ytterby 2 and 3 near the Québec-Labrador border
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.164 | 0.047 |
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".