Evidence map›Paper›PMID 40647862›Full record

ArticlePolymers2025

Prediction of Thermomechanical Behavior of Wood-Plastic Composites Using Machine Learning Models: Emphasis on Extreme Learning Machine.

Xueshan Hua, Yan Cao, Baoyu Liu, Xiaohui Yang, Hailong Xu, Lifen Li, Jing Wu

Abstract read
In one paragraph

Article in Polymers, 2025. 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

7 authors.

Xueshan HuaSpecial and Key Laboratory for Development and Utilization of Guizhou Superior Bio-Based Materials, Guizhou Minzu University, Guiyang 550025, China.
Yan CaoSpecial and Key Laboratory for Development and Utilization of Guizhou Superior Bio-Based Materials, Guizhou Minzu University, Guiyang 550025, China.
Baoyu LiuSpecial and Key Laboratory for Development and Utilization of Guizhou Superior Bio-Based Materials, Guizhou Minzu University, Guiyang 550025, China.
Xiaohui YangSpecial and Key Laboratory for Development and Utilization of Guizhou Superior Bio-Based Materials, Guizhou Minzu University, Guiyang 550025, China.
Hailong XuSpecial and Key Laboratory for Development and Utilization of Guizhou Superior Bio-Based Materials, Guizhou Minzu University, Guiyang 550025, China.
Lifen LiCollege of Forestry, Guizhou University, Guiyang 550025, China.
Jing WuCollege of Data Science and Information Engineering, Guizhou Minzu University, Guiyang 550025, China.ORCID 0000-0001-7279-6181

Funding

Department of Education of Guizhou Province QianJiaoJi[2023]034Guizhou Provincial Department of Human Resources and Social Security high-level talent innovation and entrepreneurship project 2022-06National Natural Science Foundation of China 32160413, 32060324
6 · The paper itself

Abstract

The dynamic thermomechanical properties of wood-plastic composites (WPCs) are influenced by various factors, such as the selection of raw materials and processing parameters. To investigate the effects of different wood fiber content ratios and temperature on the loss modulus of WPCs, seven different proportions of Masson pine (

Indexed as

dynamic thermomechanical propertiesextreme learning machineloss modulusmachine learningwood–plastic composites

Identifiers

PMID40647862
PMCPMC12252123

What OpenQuestion holds

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LicenceCC BY
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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.