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Record W2134972829 · doi:10.1038/ismej.2007.75

The geomicrobiology of gold

2007· review· en· W2134972829 on OpenAlexaff
Frank Reith, Maggy F. Lengke, Donna Falconer, D. Craw, Gordon Southam

Bibliographic record

VenueThe ISME Journal · 2007
Typereview
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsWestern University
Fundersnot available
KeywordsArchaeaBiogeochemical cycleBacteriaEnvironmental chemistryGeomicrobiologySulfate-reducing bacteriaHot springMineralization (soil science)BiologyBiogeochemistryMicroorganismChemistryEcologyEnvironmental biotechnologySoil water

Abstract

fetched live from OpenAlex

Microorganisms capable of actively solubilizing and precipitating gold appear to play a larger role in the biogeochemical cycling of gold than previously believed. Recent research suggests that bacteria and archaea are involved in every step of the biogeochemical cycle of gold, from the formation of primary mineralization in hydrothermal and deep subsurface systems to its solubilization, dispersion and re-concentration as secondary gold under surface conditions. Enzymatically catalysed precipitation of gold has been observed in thermophilic and hyperthermophilic bacteria and archaea (for example, Thermotoga maritime, Pyrobaculum islandicum), and their activity led to the formation of gold- and silver-bearing sinters in New Zealand's hot spring systems. Sulphate-reducing bacteria (SRB), for example, Desulfovibrio sp., may be involved in the formation of gold-bearing sulphide minerals in deep subsurface environments; over geological timescales this may contribute to the formation of economic deposits. Iron- and sulphur-oxidizing bacteria (for example, Acidothiobacillus ferrooxidans, A. thiooxidans) are known to breakdown gold-hosting sulphide minerals in zones of primary mineralization, and release associated gold in the process. These and other bacteria (for example, actinobacteria) produce thiosulphate, which is known to oxidize gold and form stable, transportable complexes. Other microbial processes, for example, excretion of amino acids and cyanide, may control gold solubilization in auriferous top- and rhizosphere soils. A number of bacteria and archaea are capable of actively catalysing the precipitation of toxic gold(I/III) complexes. Reductive precipitation of these complexes may improve survival rates of bacterial populations that are capable of (1) detoxifying the immediate cell environment by detecting, excreting and reducing gold complexes, possibly using P-type ATPase efflux pumps as well as membrane vesicles (for example, Salmonella enterica, Cupriavidus (Ralstonia) metallidurans, Plectonema boryanum); (2) gaining metabolic energy by utilizing gold-complexing ligands (for example, thiosulphate by A. ferrooxidans) or (3) using gold as metal centre in enzymes (Micrococcus luteus). C. metallidurans containing biofilms were detected on gold grains from two Australian sites, indicating that gold bioaccumulation may lead to gold biomineralization by forming secondary 'bacterioform' gold. Formation of secondary octahedral gold crystals from gold(III) chloride solution, was promoted by a cyanobacterium (P. boryanum) via an amorphous gold(I) sulphide intermediate. 'Bacterioform' gold and secondary gold crystals are common in quartz pebble conglomerates (QPC), where they are often associated with bituminous organic matter possibly derived from cyanobacteria. This may suggest that cyanobacteria have played a role in the formation of the Witwatersrand QPC, the world's largest gold deposit.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.063
GPT teacher head0.332
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations229
Published2007
Admission routes1
Has abstractyes

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