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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

88
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
88
Improving Translational Accuracy02:07

Improving Translational Accuracy

11.7K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
11.7K
Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

4.6K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
4.6K
DNA as a Genetic Template02:05

DNA as a Genetic Template

6.9K
6.9K
Introduction to Learning01:18

Introduction to Learning

493
Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
493
Stereotype Content Model02:16

Stereotype Content Model

14.8K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.8K

You might also read

Related Articles

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

Sort by
Same journal

Can Evidential Pluralism mitigate bias and motivated reasoning?

Synthese·2026
Same journal

AI-assisted rational decision-making.

Synthese·2026
Same journal

Technological Understanding: On the cognitive skill involved in the design and use of technological artefacts.

Synthese·2026
Same journal

Addictive Motivational Scaffolds and the Structure of Social Media.

Synthese·2026
Same journal

When do we experience effort?

Synthese·2026
Same journal

Prescriptive 'selves' and self-illness ambiguity.

Synthese·2025
See all related articles

Related Experiment Video

Updated: Aug 6, 2025

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

63

How localized are computational templates? A machine learning approach.

Maximilian Noichl1,2

  • 1Faculty of Philosophy and Education, University of Vienna, Universitätsstraße 7, 1010 Vienna, Austria.

Synthese
|March 20, 2023
PubMed
Summary
This summary is machine-generated.

This study uses science mapping to analyze interdisciplinary connections, revealing formulaic structures common across diverse scientific fields and their modeling techniques.

Keywords:
Computational philosophyComputational templatesDigital humanitiesFormulasModel templatesModeling practiceScience mapping

More Related Videos

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.3K

Related Experiment Videos

Last Updated: Aug 6, 2025

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

63
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.3K

Area of Science:

  • Explores the interconnectedness of scientific disciplines, moving beyond traditional linear models.
  • Focuses on the transfer of modeling techniques across fields.

Background:

  • Traditional view: sciences connect linearly (math to social sciences).
  • Interdisciplinary research often studied via limited case studies.
  • Existing research complicates the linear model with orthogonal connections.

Purpose of the Study:

  • Propose science mapping techniques for analyzing large-scale interdisciplinary connections.
  • Investigate connections between modeling techniques across multiple scientific disciplines.
  • Provide a quantitative supplement to qualitative case study approaches.

Main Methods:

  • Detailed explanation of modern science mapping techniques.
  • Application to a large, multidisciplinary dataset (383,961 articles).
  • Comparison of textual and mathematical representations in scientific literature.

Main Results:

  • Identification of formulaic structures prevalent across different disciplines.
  • Quantitative data on the strength and commonality of interdisciplinary relationships.
  • Demonstration of science mapping's utility in understanding scientific connections.

Conclusions:

  • Science mapping offers a robust method for studying large-scale interdisciplinary relations.
  • Formulaic structures represent a significant, quantifiable aspect of cross-disciplinary modeling.
  • Findings challenge simplistic linear views of scientific integration.