The Blackwater gold-spessartine-pyrolusite glacial dispersal train, British Columbia, Canada: Influence of sampling depth on indicator mineralogy and geochemistry
Bibliographic record
Abstract
A comprehensive program of indicator mineral and geochemical sampling of both oxidized and unoxidized till at the glaciated Blackwater Au-Ag deposit in the interior of south-central British Columbia, Canada has provided key insights into glacial and post-glacial dispersal patterns that can be used to explore other glaciated regions more effectively. The Blackwater deposit is located on the northeastern slope of Mount Davidson and is completely covered by till that was deposited by NE-flowing ice. Only the sulphide-depleted supergene cap of the deposit was exposed to the ice. Indicator mineral sampling of C-horizon till on the mountain slope identified a 1.3 km wide gold grain dispersal train that extends c. 3 km glacially down-ice and 200 vertical metres down-slope from the deposit. The till within this train contains from 10 to 641 gold grains, dominantly of 25 µm size, per 10 kg of its <2 mm matrix. As well, the 0.25 – 0.5 mm fraction contains up to 25 000 grains per sample of spessartine garnet derived from the hypogene alteration envelope of the Blackwater deposit, increasing the probable detectable length of the train to 10 km. Geochemically, in the <0.063 mm fraction of the till, the detectable length of the train is reduced to <1 km, with the best indicator elements being Au and Zn. In drill holes, the host till is oxidized to a depth of 2 – 5 m. It thickens markedly downslope from a few metres to c. 100 m. The gold-spessartine dispersal train thickens sympathetically to nearly 30 m and also ascends progressively within the till section. Gold grain and spessartine levels in the unoxidized till at depth are similar to those in the oxidized till at surface but the unoxidized till also contains up to 60 000 grains per sample of metal-rich pyrolusite derived from supergene cap of the Blackwater deposit.
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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 | 0.001 | 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) | 0.001 | 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".