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Record W4416711768 · doi:10.1139/cjm-2025-0037

Isolation of marine bacteria through a “bait” approach

2025· article· en· W4416711768 on OpenAlexafffundvenue
Bahar Pakseresht, Zachary Schiffman, Susan McLatchie, Pascale Coulombe, Safiya Soullane, Anic Imfeld, Yves Gélinas, David A. Walsh, Brandon Findlay

Bibliographic record

VenueCanadian Journal of Microbiology · 2025
Typearticle
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsConcordia University
FundersConcordia University
KeywordsMyxobacteriaMarine bacteriophageBacteriaIsolation (microbiology)16S ribosomal RNAEstuaryMicroorganismMarine species

Abstract

fetched live from OpenAlex

There is a great divide between the microbes active in natural environments and the organisms that may be grown in a laboratory setting. In this work we set out to cultivate representatives of the marine myxobacterial clade, a highly diverse, largely uncultured group of Gram-negative bacteria believed to have extensive biosynthetic potential. Sediment samples were collected from the St. Lawrence Estuary and Gulf and the presence of active marine myxobacteria was established through qPCR analysis of 16S rRNA gene and transcript abundances. In the expectation that the marine myxobacteria would exhibit predatory behaviour like their terrestrial counterparts, the sediment samples were then streaked on agar plates that contained common marine bacteria as the sole carbon source. Unexpectedly, in place of myxobacteria we isolated Pseudomonas, Bacillus, and Stenotropomonas spp., among others, revealing a generalized ability for these strains to break down living organic matter and suggesting that “bait” bacteria may be an effective approach for the cultivation of novel marine saprophytes.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.003

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 head0.012
GPT teacher head0.226
Teacher spread0.214 · 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 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

Citations0
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Microbiology→Same topicMicrobial Natural Products and Biosynthesis→French-language works237,207→