Jove
Visualize
联系我们

相关概念视频

Censoring Survival Data01:09

Censoring Survival Data

82
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
82
RACE - Rapid Amplification of cDNA Ends02:35

RACE - Rapid Amplification of cDNA Ends

6.3K
Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific...
6.3K
RNA-seq03:21

RNA-seq

9.9K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
9.9K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

AI derived Whole-Body MRI metrics in multiple myeloma patients reveal unique insights into body composition and outcomes.

Blood advances·2026
Same author

Evaluating the Real-World Value of Daratumumab Addition to Multiple Myeloma Induction Therapy by Real-World Minimal Residual Disease Assessment and Extended Genetic Profiling.

Clinical lymphoma, myeloma & leukemia·2025
Same author

Indonesia Election Archive: Institutions, candidates and results.

Scientific data·2025
Same author

The Adolescent Immunization Platform: The Past and Future.

The Journal of adolescent health : official publication of the Society for Adolescent Medicine·2025
Same author

Real-world use of venetoclax in the treatment of paediatric and teenage/young adult haematological malignancies.

British journal of haematology·2024
Same author

A Problem Shared Is a Community Created: Recommendations for Cross-Institutional Collaborations.

Journal of escience librarianship·2024
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关实验视频

Updated: Jun 26, 2025

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

12.1K

使用机器编码:机器辅助编码罕见事件数据.

Henry David Overos1, Roman Hlatky2, Ojashwi Pathak1

  • 1Government and Politics, University of Maryland at College Park, College Park, MD, USA.

PNAS nexus
|May 20, 2024
PubMed
概括
此摘要是机器生成的。

大型语言模型 (LLM) 对机器编码有希望,但验证仍然至关重要. GPT-4在熟悉的环境中展示了专家级别的表现,强调了严格的LLM评估的必要性.

关键词:
贝尔特 (BERT) 公司在 GPT 中,GPT 必须是 GPT.机器编码 机器编码机器学习是机器学习.政治事件数据 事件数据

更多相关视频

Automated Detection and Analysis of Exocytosis
13:28

Automated Detection and Analysis of Exocytosis

Published on: September 11, 2021

3.5K
Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.5K

相关实验视频

Last Updated: Jun 26, 2025

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

12.1K
Automated Detection and Analysis of Exocytosis
13:28

Automated Detection and Analysis of Exocytosis

Published on: September 11, 2021

3.5K
Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.5K

科学领域:

  • 政治科学 政治科学是指政治学.
  • 计算社会科学 计算社会科学
  • 人工智能的人工智能

背景情况:

  • 使用LLM的机器编码已经取得了重大进展,但对LLM分类的可靠性和验证存在担忧.
  • 根据提示,调整,学科,任务,特别是零射击应用程序,LLM的性能有所不同.

研究的目的:

  • 评估监督和半监督的机器编码算法在政治学中的性能.
  • 将三个LLM模型的性能相互比较,并与训练有素的人类专家进行比较.
  • 评估快速工程和数据预处理对LLM编码准确性的影响.

主要方法:

  • 在政治数据上使用监督和半监督学习的三个LLM模型的比较分析.
  • 模型性能测试的多次代,使用不同的提示工程和数据预处理技术.
  • 在更新的数据集上对LLM绩效的评估,以减轻培训前偏见的担忧.

主要成果:

  • 在编码熟悉的环境中,GPT-4的表现与训练有素的人类专家相美.
  • 编码中的LLM一致性在不同的环境中有所不同,GPT-4显示出更高的一致性.
  • 快速工程和数据预处理影响了LLM的性能,但在特定场景中,GPT-4主要实现了专家级编码.

结论:

  • 只有GPT-4接近训练有素的专家编码人员对政治数据的表现,特别是在熟悉的环境中.
  • LLM编码提供了潜在的好处,但需要仔细验证和考虑缺点可靠的应用.
  • 需要进一步的研究来完善LLM验证方法,并确保在各种编码任务中保持一致的性能.