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Related Concept Videos

Variability: Analysis01:11

Variability: Analysis

143
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
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Types of Impact01:30

Types of Impact

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Impacts can be classified in various forms, primarily under two subgroups: central impact and oblique impact. A central impact occurs when two objects collide head-on, possessing opposite velocities aligned along the line of impact. Conversely, an oblique impact occurs when two objects collide at an angle, resulting in a modification of both direction and velocity.
The coefficient of restitution is a metric for understanding the dynamics of impacts. It quantifies the ratio of relative velocity...
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Impact01:30

Impact

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Impact occurs when two bodies collide, leading to the application of impulsive forces between them. Analyzing impact mechanics involves considering two colliding particles moving along a line known as the line of impact, which passes through their centers and is perpendicular to the contact plane.
When particles with different initial velocities collide, they induce deformation by applying equal and opposite impulses. At the point of maximum deformation, the particles move together with...
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Impact Loading01:19

Impact Loading

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Impact loading occurs when a moving object collides with a stationary structure, such as a rod with a uniform cross-sectional area fixed at one end. Under these conditions, the rod absorbs the kinetic energy from the striking object, leading to deformation and subsequent stress development. As the rod returns to its original position and reaches maximum stress, the absorbed energy, initially manifested as kinetic energy, transforms entirely into strain energy.
In cases of elastic deformation,...
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Genetic Variation01:25

Genetic Variation

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Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
Genes exist in different versions called alleles,...
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Variation01:19

Variation

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An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard deviation, which is the square root of variance.
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
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Variations in Citations Across Databases: Implications for Journal Impact Factors.

Khaled Moustafa1

  • 1The Arabic Preprint Server (ArabiXiv), Paris, France.

Seminars in Ophthalmology
|February 28, 2024
PubMed
Summary
This summary is machine-generated.

Journal Impact Factor (JIF) accuracy is questionable due to citation count variations across databases. Google Scholar shows higher counts, while Web of Science, used for JIF, underestimates them, impacting journal rankings.

Keywords:
Journal impact factor (JIF)citaion indexcitation analysiscitation biascitation discrepancyclarivate analyticsgoogle scholar: journal rankinghighly cited authorshighly cited journaljournal citation report

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Area of Science:

  • Bibliometrics
  • Scholarly Communication
  • Scientific Publishing

Background:

  • The Journal Impact Factor (JIF) is a key metric for evaluating journal prestige.
  • JIF calculations rely on citation data from specific databases, primarily Web of Science.
  • Concerns exist regarding the accuracy and comprehensiveness of citation data used in JIF calculations.

Purpose of the Study:

  • To assess the accuracy of Journal Impact Factor (JIF) values.
  • To compare citation counts across multiple bibliographic databases for a set of publications.
  • To identify discrepancies in citation data and their implications for JIF calculations.

Main Methods:

  • Compared citation counts for 30 publications across six databases: CrossRef, Web of Science, Publisher records, Google Scholar, PubMed, and Scopus.
  • Analyzed the range and percentage differences in citation counts between databases.
  • Evaluated the performance of Web of Science data in relation to other sources.

Main Results:

  • Significant variations in citation counts (10% to over 50%) were observed between databases.
  • Google Scholar reported the highest citation counts, while PubMed reported the lowest.
  • Web of Science data tended to underestimate citation counts compared to other sources, raising concerns about JIF accuracy.

Conclusions:

  • Current JIF calculations may not accurately reflect a journal's true impact due to underestimation by key data sources like Web of Science.
  • There is a need for more comprehensive citation data collection, potentially integrating multiple sources.
  • The fundamental definition and usage of JIF may contain inherent biases that refinements alone cannot fully address.