区分学术科学写作与人类或ChatGPT,准确度超过99%,使用现成的机器学习工具
Heather Desaire1,2, Aleesa E Chua1, Madeline Isom1
1Department of Chemistry, University of Kansas, Lawrence, KS 66045, USA.
概括
一种新的方法使用20个特征准确地区分人类学术写作和人工智能生成的文本. 这种人工智能 (AI) 检测模型达到99%以上的准确性,有助于学术诚信.
科学领域:
- 自然语言处理自然语言处理.
- 人工智能伦理学 人工智能伦理学
- 学术诚信 学术诚信
背景情况:
- 人工智能写作工具的广泛采用,如ChatGPT,需要方法来区分人工智能生成的内容和人类写作.
- 面对不断发展的AI能力,确保学术工作的真实性至关重要.
研究的目的:
- 开发和验证监督分类方法,以区分学术科学家撰写的文本和人工智能生成的文本.
- 识别人类学术写作与人工智能生成文本的独特语言特征.
主要方法:
- 利用监督分类技术,使用一组20个不同的特征.
- 分析文本的特征,如段落长度和使用模两可的语言 (例如",但是"",然而"",尽管").
主要成果:
- 在区分人类学术写作与人工智能生成的文本方面实现了超过99%的分类准确性.
- 确定了在学术环境中表明人类作者的特定语言模式.
结论:
- 开发的方法提供了一个非常准确的方法来检测人工智能生成的学术写作.
- 这一策略具有适应性,使得在学术界和其他领域创建可访问的AI检测工具成为可能.
更多相关视频
05:47Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
318
07:10Depletion of Mouse Cells from Human Tumor Xenografts Significantly Improves Downstream Analysis of Target Cells
Published on: July 29, 2016
12.7K
相关概念视频
Non-equilibrium in the Cell
4.5K
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...
4.5K
Improving Translational Accuracy
11.6K
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...
11.6K
Quantifying and Rejecting Outliers: The Grubbs Test
1.7K
Sometimes, a data set can have a recorded numerical observation that greatly deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier. To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
1.7K
Accuracy, limits, and approximation
478
Accuracy, limits, and approximations are common in many fields, especially in engineering calculations. These concepts are imperative for ensuring that a given value is as close as possible to its true value.
Accuracy is defined as the closeness of the measured value to the true or actual value. In engineering mechanics, repeated measurements are taken during theoretical or experimental analyses to ensure that the result is precise and accurate.
The accuracy of any solution is based on the...
Accuracy is defined as the closeness of the measured value to the true or actual value. In engineering mechanics, repeated measurements are taken during theoretical or experimental analyses to ensure that the result is precise and accurate.
The accuracy of any solution is based on the...
478
Accuracy and Precision
9.8K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. Highly accurate...
9.8K
