The significance of copper concentrations in natural gold alloy for reconnaissance exploration and understanding gold-depositing hydrothermal systems
Bibliographic record
Abstract
Analytical studies of placer (detrital) gold grains, intended to track bedrock sources and styles of mineralization, mainly consider alloy Ag content and inclusion mineralogy to generate ‘microchemical signatures’. Occasionally Hg and Pd help discriminate gold from different sources; Cu infrequently because electron microprobes seldom detect the low concentrations. Reporting of Cu has been largely confined to gold from porphyry–epithermal environments, and this has biased subsequent interpretations of observed Cu-bearing gold alloys. This study focuses on placer gold in the Mourne Mountains, Northern Ireland, where auriferous bedrock remains undiscovered and the complex geology is consistent with either orogenic or intrusion-related mineralization. Over 500 gold grains analysed average 0.17% Cu ranging to >1% Cu and show a wide variation in Ag content. Inclusion mineralogy mainly matches that of orogenic gold elsewhere in the host terrane; however, some signatures are suggestive of zonation within an orogenic hydrothermal mineralizing system, or possibly metamorphic-hydrothermal remobilized gold associated with subsequent intrusive activity. One locality in the study area has placer gold of a distinctive Cu-rich alloy composition containing Cu sulphide inclusions, an association noted elsewhere in gold derived from alkali Cu-Au porphyries. Consideration of Cu-bearing gold alloys worldwide indicates that previously proposed compositional correlations with deposit type are of limited value. We show that Cu contents to at least 0.8% are permissible within orogenic gold – the first time that such compositions have been clearly ascribed to orogenic mineralization. The result is particularly important considering on-going exploration in northern Canada which employs gold grain analysis to help define exploration targets.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".