Biogenicity of gold- and silver-bearing siliceous sinters forming in hot (75°C) anaerobic spring-waters of Champagne Pool, Waiotapu, North Island, New Zealand
Bibliographic record
Abstract
Champagne Pool, a large hot spring at Waiotapu in North Island, New Zealand, is rimmed by a subaerial sinter dam and a shallow subaqueous shelf that is composed of orange sinter rich in metallic sulphides. Orange siliceous flocs, also rich in sulphides, are in constant circulation in the spring pool and form loose sediment on the shelf. The orange sinters and flocs are rich in As, Sb, Tl, and Hg, and have high concentrations of Au (>100 ppm) and Ag (>330 ppm). Most metallic sulphides are amorphous and disseminated throughout the sinter, instead of forming distinct mineral phases. The shelf sinters are domal and resemble stromatolites. The neutral chloride waters (pH 5.5; temperature 75°C), however, are virtually anaerobic. Examination of the sinters by scanning electron microscopy confirms that they are laminated and contain an abundant, low-diversity assemblage of filamentous, bacilliform, and coccoid microbes. The flocs are similarly composed of very small, silicified filaments. Silicification involved replacement of the cell walls and extensive encrustation by opal-A. Based on size and morphology, these microbes are probably anaerobic bacteria or archaea. By providing substrates for nucleation of the silica, the microbes are indirectly contributing to the formation of the gold-bearing sinters.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".