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Record W2989793387 · doi:10.3390/microorganisms7120601

Extreme Environments and High-Level Bacterial Tellurite Resistance

2019· review· en· W2989793387 on OpenAlexafffund
Chris Maltman, Vladimir Yurkov

Bibliographic record

VenueMicroorganisms · 2019
Typereview
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBacteriaResistance (ecology)BiologyMicrobiologyEcologyGenetics

Abstract

fetched live from OpenAlex

Bacteria have long been known to possess resistance to the highly toxic oxyanion tellurite, most commonly though reduction to elemental tellurium. However, the majority of research has focused on the impact of this compound on microbes, namely E. coli, which have a very low level of resistance. Very little has been done regarding bacteria on the other end of the spectrum, with three to four orders of magnitude greater resistance than E. coli. With more focus on ecologically-friendly methods of pollutant removal, the use of bacteria for tellurite remediation, and possibly recovery, further highlights the importance of better understanding the effect on microbes, and approaches for resistance/reduction. The goal of this review is to compile current research on bacterial tellurite resistance, with a focus on high-level resistance by bacteria inhabiting extreme environments.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.093
GPT teacher head0.276
Teacher spread0.182 · 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.

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

Citations27
Published2019
Admission routes2
Has abstractyes

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