Evidence map›Paper›PMID 42076776›Full record

ArticleVeterinary sciences2026

Extraction of Kinematic Parameters and Comparative Study of Endurance Levels in Mongolian Horses.

Yakai Shen, Lide Su, Yong Zhang, Jin Liu, Zhihao Zhang, Shun Zhang

Abstract read
In one paragraph

Article in Veterinary sciences, 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
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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

6 authors.

Yakai ShenCollege of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China.
Lide SuCollege of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China.
Yong ZhangCollege of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China.
Jin LiuCollege of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China.
Zhihao ZhangCollege of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China.
Shun ZhangModern Agriculture and Animal Husbandry Development Center, Bayannur, Inner Mongolia Autonomous Region, Bayannur 015001, China.

Funding

Inner Mongolia Autonomous-Class Discipline Project YLXKZX-NND-049Inner Mongolia Autonomous Education Institution Innovation Team NMGIRT2312National Natural Science Foundation of China-study on the spatitemporal motion mechanism and genetic mechanisms of Mongolian horse limbs based on multi-feature fusion 32360856
6 · The paper itself

Abstract

Mongolian horses are an indigenous Chinese breed known for their endurance capacity, yet quantitative descriptions of their gait-related kinematic characteristics remain limited. This pilot exploratory study aimed to describe the kinematics of Mongolian horses during walk, slow trot, and fast trot, and to examine whether selected variables differed between race-result groups in a 12 km endurance race. Forty-six horses were classified into an excellent group and an ordinary group based on the result of a single race. Kinematic data were collected using optical motion capture and three-dimensional skeletal modelling. Separate gait-specific linear mixed-effects models were fitted, with horse identity as a random effect and group and speed as fixed effects. The results showed gait-dependent between-group differences. During walk, the excellent group had significantly greater range of motion of the tarsal, hip, and elbow joints, as well as a greater maximum forelimb retraction angle (all

Indexed as

endurance-race performancekinematic parametersMongolian horsemotion captureskeletal model

Identifiers

PMID42076776
PMCPMC13119970

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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.