The mercury and silver contents of gold in quartz vein deposits, Otago Schist, New Zealand
Bibliographic record
Abstract
Abstract A regional study of gold from Otago Schist vein deposits from both Caples and Torlesse Terranes has revealed the presence of both Au‐Ag and Au‐Ag‐Hg alloys in both terranes. Almost all Hg‐bearing gold occurs in east Otago vein systems, and Hg‐free gold occurs in central and northwest Otago vein systems, irrespective of host terrane. One Central Otago mineralised zone has up to 1.7 wt% Hg in the gold. Au‐Ag alloy (3–8 wt% Ag) is typical for gold found in most Torlesse‐hosted vein deposits, and Au‐Ag‐Hg alloys with 1–4 wt% Hg are found in vein material from the Torlesse‐hosted Hyde‐Macraes Shear Zone. Au‐Ag‐Hg alloy (3–8 wt% Ag, 2–8 wt% Hg) is found in many Caples‐hosted vein deposits. There is no relationship between depth of vein emplacement and Hg content of gold, as both high and low Hg gold are found in shallow‐formed (<2 km) and deep‐formed (>6 km) deposits. There is no spatial relationship between Hg‐bearing gold and cinnabar‐bearing veins that occur in Caples Terrane rocks on the southern edge of the schist belt. Mercury‐bearing placer gold in eastern Southland may have been derived from erosion of east Otago veins. The source of Hg‐bearing placer gold in northern Southland is unknown as yet.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".