Evidence map›Paper›PMID 41345503›Full record

ArticleScientific reports2025

Multi-indicator feature extraction and temperature prediction model for spontaneous coal combustion and oxidation.

Xuming Shao, Xiaojun Zhang, Wenhao Liu, Yanchang Li, Jinzhang Jia, Zhongxing Li, Yu Liu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 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.

Xuming ShaoSafety Science and Engineering College, Liaoning Technical University, Huludao, Liaoning, 125105, China.
Xiaojun ZhangSchool of Emergency Management and Safety Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China. 18342810199@163.com.
Wenhao LiuGuangxi Technological College of Machinery and Electricity, Nanning, 530007, Guangxi, China.
Yanchang LiSafety Science and Engineering College, Liaoning Technical University, Huludao, Liaoning, 125105, China.
Jinzhang JiaSafety Science and Engineering College, Liaoning Technical University, Huludao, Liaoning, 125105, China.
Zhongxing LiShandong Energy Group Construction Group Co., Ltd, Taian, 273500, Shangdong, China.
Yu LiuSafety Science and Engineering College, Liaoning Technical University, Huludao, Liaoning, 125105, China.

Funding

National Natural Science Foundation of China 52374203
6 · The paper itself

Abstract

Spontaneous combustion of coal poses a serious threat to mine safety, making accurate temperature prediction essential for early warning and risk prevention. This study develops a robust, data-driven prediction model capable of capturing the nonlinear coupling between coal oxidation gases and temperature evolution. Programmed heating experiments were conducted on coal samples from the Linsheng Mine to analyze the stage-wise evolution of oxidation, pyrolysis, and gas emission characteristics, identifying the critical (60-80 °C) and dry cracking (120-140 °C) temperature ranges. Twelve gas-related indicators-including six single gases (O₂, CO, CH₄, CO₂, C₂H₄, and C₂H₆) and six ratio-based variables (CO/ΔO

Indexed as

Engineering applicabilityGas indicatorsPredictive modelsProgrammed warmingSpontaneous coal combustion

Identifiers

PMID41345503
PMCPMC12780047

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.