Overview of VMS exploration in glaciated terrain using indicator minerals, till geochemistry, and boulder tracing: a Canadian perspective
Bibliographic record
Abstract
During the Quaternary, most of Canada's landmass was covered by ice sheets that eroded and dispersed metal-rich debris from volcanogenic massive sulphide (VMS) deposits across the landscape together with a blanket of unconsolidated debris. Therefore, boulder tracing, till geochemistry, and indicator minerals are important exploration methods for VMS deposits in Canada. This paper provides an overview of the development and application of these methods, including till sampling, appropriate size fractions of till to analyze, sample processing, and analytical techniques. Selected case histories from different regions across Canada are also presented. Copper, Pb, and Zn are indicator elements of VMS deposits, and pathfinder elements include As, Ag, Au, Ba, Bi, Cd, Hg, In, Sb, Se, Sn, and Tl. Abundances of these elements are most commonly determined in the <0.063 mm (silt + clay) fraction of till. Indicator minerals of VMS deposits are recovered from the >3.2 specific gravity heavy mineral concentrate of till and include the main ore minerals (galena, sphalerite, chalcopyrite, pyrite, and pyrrhotite), accessory minerals (native gold, electrum, cassiterite, cinnabar, and barite), and, in metamorphic terrain, metamorphosed minerals of mineralization, alteration, or exhalites, including sillimanite, andalusite, gahnite, staurolite, and spessartine. Magnetite and its chemical composition may also be a useful VMS exploration tool. Ongoing and future research of drift exploration methods for VMS deposits will focus on reducing sample size, lowering analytical costs, and identifying new indicator minerals and chemical discrimination criteria.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".