ArticleSports (Basel, Switzerland)2023
Profiling the Physical Performance of Young Boxers with Unsupervised Machine Learning: A Cross-Sectional Study.
Article in Sports (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06269848 (Talent Identification in Young Boxers Form the State of Mexico), which is not on this map. Cited by 6 papers.
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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.
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.
Talent Identification in Young Boxers Form the State of Mexico
Who cites it
6 citing papers in PubMed.
- Absolute Aerobic Capacity Predominates over Body Composition and Regional Anthropometry in Explaining Maximal Fat Oxidation in National-Team Collegiate Athletes: A Cross-Sectional Study.Journal of functional morphology and kinesiology · 2026Article
- Kinematic and kinetic differences between lead and rear straight punches in elite boxers: bilateral asymmetry and training implications.BMC sports science, medicine & rehabilitation · 2026Article
- Applications and Benefits of Dietary Supplements in Taekwondo: A Systematic Review.Life (Basel, Switzerland) · 2025Review
- An active machine learning framework for automatic boxing punch recognition and classification using upper limb kinematics.PloS one · 2025Article
- Case Report: Anthropometric profile and weight control strategies in a world boxing champion.Frontiers in sports and active living · 2025Article
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Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mexico City is the location with the largest number of boxers in Mexico; in fact, it is the first city in the country to open a Technological Baccalaureate in Education and Sports Promotion with a pugilism orientation. This cross-sectional study aimed to determine the physical-functional profile of applicants for admission to the baccalaureate in sports. A total of 227 young athletes (44F; 183M; 15.65 (1.79) years; 63.66 (14.98) kg; >3 years of boxing experience) participated in this study. Body mass (BM), maximal isometric handgrip (HG) strength, the height of the countermovement jump (CMJ), the velocity of straight boxing punches (PV), and the rear hand punch impact force (PIF) were measured. The young boxers were profiled using unsupervised machine learning algorithms, and the probability of superiority (ρ) was calculated as the effect size of the differences. K-Medoids clustering resulted in two sex-independent significantly different groups: Profile 1 (
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Registered trials
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