Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Numerical Calculations01:24

Numerical Calculations

1.3K
In engineering applications, the representation of the numerical value is critical. Presenting or reporting the answer is one of the essential parts of engineering practices. Numerical calculations are performed using handheld calculators or computers since numerically accurate answers are always preferred.
The solution to a problem is obtained using different methods. While manually solving algebraic symbols is one of the most common methods, the graphical method is often preferred. Computers...
1.3K
Uncertainty in Measurement: Significant Figures03:34

Uncertainty in Measurement: Significant Figures

57.9K
All the digits in a measurement, including the uncertain last digit, are called significant figures or significant digits. Note that zero may be a measured value; for example, if a scale that shows weight to the nearest pound reads “140,” then the 1 (hundreds), 4 (tens), and 0 (ones) are all significant (measured) values.
57.9K
Rules for Significant Figures01:44

Rules for Significant Figures

35.3K
In any measurement, the precision of the measuring tool is an essential factor. An ordinary ruler, for example, can measure length to the closest millimeter; a caliper, on the other hand, can measure length to the nearest 0.01 mm. As a result, the caliper is a more precise measurement tool because it can measure extremely minute changes in length. The measurements will be more accurate if the measuring tool is more precise.
It should be emphasized that when we represent measured values, the...
35.3K
Uncertainty in Measurement: Reading Instruments02:46

Uncertainty in Measurement: Reading Instruments

37.6K
Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
37.6K
How Data are Classified: Numerical Data00:59

How Data are Classified: Numerical Data

27.1K
Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
27.1K
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

2.9K
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
2.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Sensitivity of a model oscillator to shifts in the voltage-dependence of one or more ionic currents.

Journal of neurophysiology·2026
Same author

Blue plaque review series: Thomas Graham Brown: Before his time.

Experimental physiology·2026
Same author

Quantitative Neuropeptidomics Reveals Thermal Acclimation-Induced Remodeling of Peptidergic Signaling in the American Lobster <i>Homarus americanus</i>.

bioRxiv : the preprint server for biology·2026
Same author

Temperature and pH-dependent potassium currents of muscles of the stomatogastric nervous system of the crab, <i>Cancer borealis</i>.

iScience·2026
Same author

Persistent adaptation through dual-timescale regulation of ion channel properties.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

The combined effects of temperature and salinity on the stomatogastric nervous system of two species of decapod crustacea.

Journal of neurophysiology·2026
Same journal

The exquisite mechanics of a tsetse bite.

eLife·2026
Same journal

Distinct involvements of the subthalamic nucleus subpopulations in reward-biased decision-making in monkeys.

eLife·2026
Same journal

Pink1-mediated mitophagy in the endothelium releases proteins encoded by mitochondrial DNA and activates neutrophil responses during inflammation.

eLife·2026
Same journal

Restraint of melanoma progression by cells in the local skin environment.

eLife·2026
Same journal

Brawn before bite in endemic Asian eutherian mammals after the end-Cretaceous extinction.

eLife·2026
Same journal

Experimental evolution to thermal stress indicates climate resilience in a cosmopolitan arthropod.

eLife·2026
See all related articles

Related Experiment Video

Updated: May 1, 2026

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

2.3K

In numbers we trust?

Eve Marder1

  • 1Eve Marder is an eLife senior editor, and is in the Department of Biology and the Volen National Center for Complex Systems, Brandeis University, Waltham, United States marder@brandeis.edu.

Elife
|April 3, 2014
PubMed
Summary
This summary is machine-generated.

Researchers meticulously validate experimental data but often overlook the inconsistent citation and view counts of scientific publications. This inconsistency raises questions about the reliability of bibliometric data in scientific research evaluation.

Keywords:
article-level metricseLifeliving sciencepublishingresearch assessmentscientific publishing

More Related Videos

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
10:58

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

Published on: August 28, 2021

4.1K
Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
16:23

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Published on: February 26, 2014

13.6K

Related Experiment Videos

Last Updated: May 1, 2026

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

2.3K
Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
10:58

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

Published on: August 28, 2021

4.1K
Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
16:23

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Published on: February 26, 2014

13.6K

Area of Science:

  • Bibliometrics
  • Scientific Publishing
  • Research Evaluation

Background:

  • Scientific rigor demands careful data collection and analysis.
  • Bibliometric indicators like citation counts and view data are increasingly used to assess research impact.
  • Inconsistencies exist in how these bibliometric data are collected and interpreted.

Purpose of the Study:

  • To highlight the discrepancy in data standards between experimental results and bibliometric metrics.
  • To question the reliability of citation and view counts as primary measures of research value.
  • To advocate for more rigorous evaluation of bibliometric data.

Main Methods:

  • Critical analysis of current practices in scientific data handling.
  • Examination of the methodologies behind citation tracking and article view counts.
  • Discussion of the implications of inconsistent bibliometric data.

Main Results:

  • Experimental data undergo stringent validation, unlike bibliometric data.
  • Citation and view counts can be influenced by various factors, leading to potential inaccuracies.
  • The application of differing standards undermines the objective assessment of scientific contributions.

Conclusions:

  • There is a need to apply consistent and rigorous standards to bibliometric data.
  • Rethinking the reliance on potentially flawed citation and view metrics is crucial for accurate research evaluation.
  • Promoting transparency and standardization in bibliometric data collection is essential.