Evidence map›Paper›PMID 36559598›Full record

ArticlePlants (Basel, Switzerland)2022

Association between the Classification of the Genus of Batrachospermaceae (Rhodophyta) and the Environmental Factors Based on Machine Learning.

Qiqin Yang, Fangru Nan, Xudong Liu, Qi Liu, Junping Lv, Jia Feng, Fei Wang, Shulian Xie

Abstract read
In one paragraph

Article in Plants (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Response mechanisms ofFrontiers in plant science · 2025
    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

8 authors.

Qiqin YangShanxi Key Laboratory for Research and Development of Regional Plants, School of Life Science, Shanxi University, Taiyuan 030006, China.
Fangru NanShanxi Key Laboratory for Research and Development of Regional Plants, School of Life Science, Shanxi University, Taiyuan 030006, China.
Xudong LiuShanxi Key Laboratory for Research and Development of Regional Plants, School of Life Science, Shanxi University, Taiyuan 030006, China.
Qi LiuShanxi Key Laboratory for Research and Development of Regional Plants, School of Life Science, Shanxi University, Taiyuan 030006, China.
Junping LvShanxi Key Laboratory for Research and Development of Regional Plants, School of Life Science, Shanxi University, Taiyuan 030006, China.
Jia FengShanxi Key Laboratory for Research and Development of Regional Plants, School of Life Science, Shanxi University, Taiyuan 030006, China.
Fei WangSchool of Physical Education, Shanxi University, Taiyuan 030006, China.
Shulian XieShanxi Key Laboratory for Research and Development of Regional Plants, School of Life Science, Shanxi University, Taiyuan 030006, China.ORCID 0000-0003-2349-2071

Funding

National Natural Science Foundation of China 32170204
6 · The paper itself

Abstract

Batrachospermaceae is the largest family of freshwater red algae, widely distributed around the world, and plays an important role in maintaining the balance of spring and creek ecosystems. The deterioration of the current global ecological environment has also destroyed the habitat of Batrachospermaceae. The research on the environmental factors of Batrachospermaceae and the accurate classification of the genus is necessary for the protection, restoration, excavation, and utilization of Batrachospermaceae resources. In this paper, the database of geographical distribution and environmental factors of Batrachospermaceae was sorted out, and the relationship between the classification of genus and environmental factors in Batrachospermaceae was analyzed based on two machine learning methods, random forest and XGBoost. The result shows: (1) The models constructed by the two machine learning methods can effectively distinguish the genus of Batrachospermaceae based on environmental factors; (2) The overall AUC score of the random forest model for the classification and prediction of the genus of Batrachospermaceae reached 90.41%, and the overall AUC score of the taxonomic prediction of each genus of Batrachospermaceae reached 85.85%; (3) Combining the two methods, it is believed that the environmental factors that affect the distinction of the genus of Batrachospermaceae are mainly altitude, average relative humidity, average temperature, and minimum temperature, among which altitude has the greatest influence. The results can further clarify the taxonomy of the genus in Batrachospermaceae and enrich the research on the differences in environmental factors of Batrachospermaceae.

Indexed as

Batrachospermaceaeenvironmental factorsmachine learningrandom forestXGBoost

Identifiers

PMID36559598
PMCPMC9781829

What OpenQuestion holds

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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.