Evidence map›Paper›PMID 28533766›Full record

ArticleFrontiers in microbiology2017

Predicting the HMA-LMA Status in Marine Sponges by Machine Learning.

Lucas Moitinho-Silva, Georg Steinert, Shaun Nielsen, Cristiane C P Hardoim, Yu-Chen Wu, Grace P McCormack, Susanna López-Legentil, Roman Marchant, Nicole Webster, Torsten Thomas and 1 more

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers.

0numbers the graph read from it
0cells of the map it votes in
90citing 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

90 citing papers in PubMed.

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30 more citing papers are in PubMed but not listed here.

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

11 authors.

Lucas Moitinho-SilvaCentre for Marine Bio-Innovation, University of New South WalesSydney, NSW, Australia.
Georg SteinertLaboratory of Microbiology, Wageningen UniversityWageningen, Netherlands.
Shaun NielsenCentre for Marine Bio-Innovation, University of New South WalesSydney, NSW, Australia.
Cristiane C P HardoimDepartamento de Invertebrados, Museu Nacional, Universidade Federal do Rio de JaneiroRio de Janeiro, Brazil.
Yu-Chen WuRD3 Marine Microbiology, GEOMAR Helmholtz Centre for Ocean Research Kiel and Christian-Albrechts UniversityKiel, Germany.
Grace P McCormackZoology, Ryan Institute, School of Natural Sciences, National University of Ireland GalwayGalway, Ireland.
Susanna López-LegentilDepartment of Biology and Marine Biology, and Center for Marine Science, University of North CarolinaWilmington, NC, USA.
Roman MarchantCentre for Translational Data Science, School of Information Technologies, University of SydneySydney, NSW, Australia.
Nicole WebsterAustralian Institute of Marine ScienceTownsville, QLD, Australia.
Torsten ThomasCentre for Marine Bio-Innovation, University of New South WalesSydney, NSW, Australia.
Ute HentschelRD3 Marine Microbiology, GEOMAR Helmholtz Centre for Ocean Research Kiel and Christian-Albrechts UniversityKiel, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The dichotomy between high microbial abundance (HMA) and low microbial abundance (LMA) sponges has been observed in sponge-microbe symbiosis, although the extent of this pattern remains poorly unknown. We characterized the differences between the microbiomes of HMA (

Indexed as

16S rRNA genemarine spongesmicrobial diversitymicrobiomerandom forestsymbiosis

Identifiers

PMID28533766
PMCPMC5421222

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Registered trials

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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.