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Record W4406240126 · doi:10.3791/67426

Isolation of Soil Microorganisms Using iChip Technology

2025· article· en· W4406240126 on OpenAlexaff
L. Gauthier, Adam Foster, Brian D. Wagner, Christopher W. Kirby

Bibliographic record

VenueJournal of Visualized Experiments · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of Prince Edward IslandAgriculture and Agri-Food Canada
Fundersnot available
KeywordsMicroorganismIsolation (microbiology)MicrobiomeBiologyBacteriaSoil microbiologyAntimicrobialMicrobiologyBioinformatics

Abstract

fetched live from OpenAlex

The iChip isolation technique uses an in-situ isolation device that increases the cultivability of previously unculturable microorganisms. Microorganisms are an important source of novel chemistries and potentially bioactive molecules. However, only 1% of environmental microorganisms can be cultured using conventional laboratory methods. With the rise in antimicrobial resistance, finding new drugs to combat infections and diseases is of foremost importance, and a critical method to finding new molecules is the discovery of new microorganisms. By incubating colonies of soil microorganisms in the wells of a 96-well plate, sealed with a semipermeable membrane and incubated on top of soil, the microbes are in contact with water and growth factors from the soil, allowing for the isolation of novel microbes in a laboratory setting. After a period of domestication in an iChip, microorganisms can potentially be subcultured onto conventional media and used for further study. This device is valuable to bioactive molecule discovery and soil microbiome research and has been used previously in both applications.

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)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.005

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 head0.017
GPT teacher head0.395
Teacher spread0.377 · 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
GenreMethods

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

Citations2
Published2025
Admission routes1
Has abstractyes

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