Evidence map›Paper›PMID 39215402›Full record

ArticleMicrobial biotechnology2024

Improving the odds: Artificial intelligence and the great plate count anomaly.

Detmer Sipkema

Abstract read
In one paragraph

Article in Microbial biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Detmer SipkemaLaboratory of Microbiology, Wageningen University, Wageningen, The Netherlands.ORCID 0000-0003-3836-219X

Funding

HORIZON EUROPE Innovative Europe H2020-FNR-2020-2-101000392
6 · The paper itself

Abstract

Next-generation DNA sequencing has shown that the great plate count anomaly, that is, the difference between bacteria present in the environment and those that can be obtained in culture from that environment, is even greater and more persisting than initially thought. This hampers fundamental understanding of bacterial physiology and biotechnological application of the unculture majority. With big sequence data as foundation, artificial intelligence (AI) may be a game changer in bacterial isolation efforts and provide directions for the cultivation media and conditions that are most promising and as such be used to canalize limited human and financial resources. This opinion paper discusses how AI is or can be used to improve the success of bacterial isolation.

Indexed as

Artificial IntelligenceBacteriaBacteriological TechniquesHigh-Throughput Nucleotide Sequencing

Identifiers

PMID39215402
PMCPMC11364511

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.