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Isolation of Tellurite- and Selenite-Resistant Bacteria from Hydrothermal Vents of the Juan de Fuca Ridge in the Pacific Ocean

2002· article· en· W2151510413 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied and Environmental Microbiology · 2002
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsUniversity of British ColumbiaUniversity of Manitoba
FundersNational Science Foundation
KeywordsMetalloidHydrothermal ventHydrothermal circulationSeleniumBacteriaBiologyExtreme environmentMetalChemistry

Abstract

fetched live from OpenAlex

Deep-ocean hydrothermal-vent environments are rich in heavy metals and metalloids and present excellent sites for the isolation of metal-resistant microorganisms. Both metalloid-oxide-resistant and metalloid-oxide-reducing bacteria were found. Tellurite- and selenite-reducing strains were isolated in high numbers from ocean water near hydrothermal vents, bacterial films, and sulfide-rich rocks. Growth of these isolates in media containing K(2)TeO(3) or Na(2)SeO(3) resulted in the accumulation of metallic tellurium or selenium. The MIC of K(2)TeO(3) ranged from 1,500 to greater than 2,500 micro g/ml, and the MIC of Na(2)SeO(3) ranged from 6,000 to greater than 7,000 micro g/ml for 10 strains. Phylogenetic analysis of 4 of these 10 strains revealed that they form a branch closely related to members of the genus Pseudoalteromonas, within the gamma-3 subclass of the Proteobacteria. All 10 strains were found to be salt tolerant, pH tolerant, and thermotolerant. The metalloid resistance and morphological, physiological, and phylogenetic characteristics of newly isolated strains are described.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.593
Threshold uncertainty score0.188

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 head0.005
GPT teacher head0.149
Teacher spread0.144 · 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