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Record W2099251155 · doi:10.1144/0016-764900-131

Biogenicity of gold- and silver-bearing siliceous sinters forming in hot (75°C) anaerobic spring-waters of Champagne Pool, Waiotapu, North Island, New Zealand

2001· article· en· W2099251155 on OpenAlexaff
Brian Jones, Robin W. Renaut, Michael R. Rosen

Bibliographic record

VenueJournal of the Geological Society · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeochemistry and Elemental Analysis
Canadian institutionsUniversity of SaskatchewanUniversity of Alberta
Fundersnot available
KeywordsHot springGeologySpring (device)Bearing (navigation)GeochemistryOceanographyMineralogyPaleontologyGeographyCartographyEngineering

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.804

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.192
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations68
Published2001
Admission routes1
Has abstractyes

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