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相关概念视频

Stereotype Content Model02:16

Stereotype Content Model

14.7K
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...
14.7K
SBAR I: Understanding the Concept01:29

SBAR I: Understanding the Concept

4.5K
Effective communication among healthcare professionals during hand-off reporting is essential to delivering safe and continuous patient care. Common professional interactions include reports to healthcare team members, hand-off, and transfer reports. Nurses routinely report information to other healthcare team members and also urgently contact healthcare providers to report changes in patient status.
Standardized methods of communication have been developed to ensure that information is...
4.5K
SBAR II: Application of SBAR01:14

SBAR II: Application of SBAR

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SBAR is an effective communication tool used by healthcare professionals to communicate patient information accurately. SBAR stands for Situation, Background, Assessment, and Recommendation. For a better understanding, an example is given below.
SBAR Report from a Nurse to a Health Care Provider
S: "Hello, Dr. Smith. This is Jane, RN, from the Med Surg unit. I am calling to tell you about Ms. White in Room 210, who is experiencing increased pain and redness at her incision site. Her recent...
4.4K
Sympathetic Signaling01:32

Sympathetic Signaling

941
Sympathetic signaling, a vital part of the autonomic nervous system, plays a crucial role in mobilizing the body's resources in response to stress or emergencies. It involves the transmission of nerve impulses from sympathetic preganglionic fibers to postganglionic fibers. This results in the release of specific neurotransmitters and activation of adrenergic receptors.
Sympathetic preganglionic fibers release the neurotransmitter acetylcholine (ACh) onto the ganglionic neurons in the...
941
Fundamental Attribution Error01:14

Fundamental Attribution Error

12.8K
According to some social psychologists, people tend to overemphasize internal factors as explanations—or attributions—for the behavior of other people. They tend to assume that the behavior of another person is a trait of that person, and to underestimate the power of the situation on the behavior of others. They tend to fail to recognize when the behavior of another is due to situational variables, and thus to the person’s state. This erroneous assumption is...
12.8K
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

1.5K
Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
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...
1.5K

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相关实验视频

Updated: Jun 22, 2025

Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects
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Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects

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一种基于上下文的方法来检测刺言论.

Nivin A Helal1, Ahmed Hassan2, Nagwa L Badr1

  • 1Faculty of Computer and Information Sciences, Ain Shams University, Cairo, 11566, Egypt.

Scientific reports
|July 4, 2024
PubMed
概括

这项研究通过使用上下文线索来增强刺言论的检测. 整合上下文显著改善了模型性能,达到高达99%的准确性,并减少了训练时间.

科学领域:

  • 自然语言处理自然语言处理.
  • 计算语言学 计算语言学
  • 人工智能的人工智能

背景情况:

  • 由于依赖于孤立的发言,刺言论的检测是具有挑战性的.
  • 语境线索对于准确识别刺的意图至关重要.

研究的目的:

  • 开发一种使用上下文特征来检测刺言论的增强方法.
  • 提高识别刺在文本中的准确性和效率.

主要方法:

  • 使用预训练过的变压器模型:RoBERTa和DistilBERT.
  • 在新闻头条和末数据集上微调的模型具有上下文信息.
  • 尝试了上下文总结,以缩短培训时间.

主要成果:

  • 在新闻头条上获得了99%的F1分数,在末数据集上达到90%.
  • 语境总结减少了35.5%的培训时间.
  • 在Reddit数据集上的刺言论检测从49% (没有上下文) 提高到75% (有上下文).

结论:

  • 语境特征显著提高了刺言论检测的准确性.
  • 拟议的方法可以在不同的环境中提高对刺言论的理解.

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Last Updated: Jun 22, 2025

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  • 准确的刺言论检测有助于更好的情绪分析和决策.