Evidence map›Paper›PMID 42312183›Full record

ArticleISME communications2026

Unveiling the role of soil microorganisms in indicating paddy soil health via metagenomics combined with machine learning.

Yu-Ling Zheng, Yun-Shuo Guo, Xin-Yue Ren, Yi-Fei Wang, Hui-Ling Cui, Li-Mei Zhang, Long-Jun Ding, Yong-Guan Zhu

Abstract read
In one paragraph

Article in ISME communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Yu-Ling ZhengState Key Laboratory of Regional and Urban Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
Yun-Shuo GuoState Key Laboratory of Regional and Urban Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
Xin-Yue RenUniversity of Chinese Academy of Sciences, Beijing 100049, China.
Yi-Fei WangState Key Laboratory of Regional and Urban Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
Hui-Ling CuiState Key Laboratory of Regional and Urban Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
Li-Mei ZhangState Key Laboratory of Regional and Urban Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
Long-Jun DingState Key Laboratory of Regional and Urban Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
Yong-Guan ZhuState Key Laboratory of Regional and Urban Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.ORCID https://orcid.org/0000-0003-3861-8482

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The soil microbiome performs various ecological functions, making it a potentially vital component of soil health assessment; however, the indicator taxa of soil health remain unidentified. This study explored these taxa in paddy soils of the black soil region in Northeast China. First, the soil health index (SHI) was evaluated using representative physicochemical and biological parameters, revealing that approximately one-third of the soils had a low health level. A Random Forest model was then developed based on microbial species' relative abundance to predict the SHI, achieving an

Indexed as

indicator taxamachine learningmetagenomicspaddy soilssoil health

Identifiers

PMID42312183
PMCPMC13271413

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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.