Till geochemical signatures of the Sisson W-Mo deposit, New Brunswick
Bibliographic record
Abstract
A till composition study was carried out around the Sisson W-Mo deposit, one of the largest W deposits in the world, as part of the Geological Survey of Canadamp;gt;'s (GSC) Targeted Geoscience Initiative 4 (TGI-4), a collaborative federal geoscience program with a mandate to provide industry with the next generation of geoscience knowledge and innovative techniques that will result in more effective targeting of buried mineral deposits. This till geochemical study is one of the first detailed studies around a major W deposit in glaciated terrain. The <0.063 mm fraction of till clearly defines glacial dispersal at least 14 km down-ice of the deposit and this size fraction of till is recommended for W-Mo exploration in the region. Indicator elements for this type of W-Mo deposit include the ore elements W and Mo, and pathfinder elements Sn, Bi, Cu, Zn, Pb, Ag, In, As, Cd, Zn, and Te. A total digestion method, such as the one used in this study (lithium meta/tetraborare fusion/ICP-MS), is required to report the total concentration of W and Sn in till and aqua regia is suitable for determining the other pathfinder elements. Glacial dispersal of W and Mo from the Sisson deposit is detectable at a regional scale at least 14 km down-ice (southeast) using surface till sampling. A 2 km till sample spacing would be sufficient to detect the W dispersal train from a W-Mo deposit of this size.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".