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Record W3183263780 · doi:10.3390/d13080344

Genome Sequence of Brevundimonas sp., an Arsenic Resistant Soil Bacterium

2021· article· en· W3183263780 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

VenueDiversity · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsUniversity of Waterloo
FundersFondo Nacional de Desarrollo Científico y TecnológicoComisión Nacional de Investigación Científica y Tecnológica
KeywordsEffluxArsenicBacteriaOperonGeneBioremediationBiologyGenomeMicrobiologyStrain (injury)Whole genome sequencingMicroorganismBacterial genome sizeGeneticsChemistryEscherichia coli

Abstract

fetched live from OpenAlex

Brevundimonas sp. is a bacteria able to grow in metal(loid) contaminated soil from Puchuncaví Valley, central Chile. This study has isolated a bacterial strain capable of growth under high doses of arsenic (As) (6000 mg L−1), and a draft genome sequence was generated. Additionally, real-time PCR was performed to examine the effect of As on some genes related to As resistance. Results demonstrated a total of 3275 predicted annotated genes with several genes related to the ars operon, metal(loid) resistance-related genes, metal efflux pumps, and detoxifying enzymes. Real-time PCR showed that the arsB involved in the efflux of As was down-regulated, whereas arsR, arsH, and ACR3 did not show differences with the addition of As. Our study provides novel evidence of diverse As regulating systems in tolerant bacteria that will lead to a better understanding of how microorganisms overcome toxic elements and colonize As contaminated soils and to the possible use of their specific properties in bioremediation.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.880
Threshold uncertainty score0.998

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)0.0030.000

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 head0.024
GPT teacher head0.220
Teacher spread0.196 · 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