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Record W2913380830 · doi:10.1007/s10295-018-02121-x

A selective genome-guided method for environmental <i>Burkholderia</i> isolation

2019· article· en· W2913380830 on OpenAlexafffund
F. P. Jake Haeckl, João L. Baldim, Dasha Iskakova, Kenji L. Kurita, Marisi G. Soares, Roger G. Linington

Bibliographic record

VenueJournal of Industrial Microbiology & Biotechnology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogenic Bacteria Studies
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsIsolation (microbiology)BurkholderiaBiologyComputational biologyMicrobiologyBacteriaGenetics

Abstract

fetched live from OpenAlex

The genus Burkholderia is an emerging source of novel natural products chemistry, yet to date few methods exist for the selective isolation of strains of this genus from the environment. More broadly, tools to efficiently design selection media for any given genus would be of significant value to the natural products and microbiology communities. Using a modification of the recently published SMART protocol, we have developed a two-stage isolation protocol for strains from the genus Burkholderia. This method uses a combination of selective agar isolation media and multiplexed PCR profiling to derive Burkholderia strains from environmental samples with 95% efficiency. Creation of this new method paves the way for the systematic exploration of natural products chemistry from this important genus and offers new insight into potential methods for selective isolation method development for other priority genera.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.797

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.024
GPT teacher head0.223
Teacher spread0.200 · 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 designBench or experimental
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

Citations10
Published2019
Admission routes2
Has abstractyes

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