Colloidal transport and flocculation are the cause of the hyperenrichment of gold in nature
Bibliographic record
Abstract
Aqueous complexation has long been considered the only viable means of transporting gold to depositional sites in hydrothermal ore-forming systems. A major weakness of this hypothesis is that it cannot readily explain the formation of ultrahigh-grade gold veins. This is a consequence of the relatively low gold concentrations typical of ore fluids (tens of parts per billion [ppb]) and the fact that these "bonanza" veins can contain weight-percent levels of gold in some epithermal and orogenic deposits. Here, we present direct evidence for a hypothesis that could explain these veins, namely, the transport of the gold as colloidal particles and their flocculation in nanoscale calcite veinlets. These gold-bearing nanoveinlets bear a remarkable resemblance to centimeter-scale ore veins in many hydrothermal gold deposits and give unique insight into the scale invariability of colloidal flocculation in forming hyperenriched gold deposits. Using this evidence, we propose a model for the development of bonanza gold veins in high-grade deposits. We argue that gold transport in these systems is largely mechanical and is the result of exceptionally high degrees of supersaturation that preclude precipitation of gold crystals and instead lead to the formation of colloidal particles, which flocculate and form much larger masses. These flocculated masses aggregate locally, where they are seismically pumped into fractures to locally form veins composed largely of gold. This model explains how bonanza veins may form from fluids containing ppb concentrations of gold and does not require prior encapsulation of colloidal gold particles in silica gel, as proposed by previous studies.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".