Related Experiment Video
Updated: Jun 22, 2026

The Deese-Roediger-McDermott (DRM) Task: A Simple Cognitive Paradigm to Investigate False Memories in the Laboratory
Published on: January 31, 2017
Correction: 'Technique-based inoculation against real-world misinformation' (2023), by Roozenbeek et al.
This study corrects the article DOI, ensuring accurate citation and referencing for scientific research. Proper attribution is crucial for maintaining the integrity of scholarly communication and the scientific record.
Area of Science:
- Bibliometrics
- Scholarly Communication
Context:
- Correction of Digital Object Identifiers (DOIs) is essential for accurate record-keeping.
- Ensuring the integrity of scientific literature requires precise metadata.
Purpose:
- To correct erroneous Digital Object Identifiers (DOIs) associated with a previously published article.
- To provide accurate citation information for researchers.
Summary:
- The article DOI 10.1098/rsos.211719 has been corrected.
- This ensures the article is correctly identified and accessible.
Impact:
- Improves the reliability of scientific citations.
- Facilitates accurate retrieval of research articles.
- Upholds the standards of scholarly publishing.
More Related Videos
08:05A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers
Published on: January 5, 2018
08:53Using a Classroom-Based Deese Roediger McDermott Paradigm to Assess the Effects of Imagery on False Memories
Published on: November 14, 2018
Related Concept Videos
Confirmation Biases
Social Facilitation
Types of Errors: Detection and Minimization
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
Systematic Error: Methodological and Sampling Errors
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Accuracy and Errors in Hypothesis Testing
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5% chance...
Impression Management Techniques IV: Altercasting