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发现研究地图的未知未知与高通量自然描述
Tanay Katiyar1, Jean-François Bonnefon2, Samuel A Mehr3,4
1Institut Jean Nicod, Département d'études cognitives, École normale supérieure (ENS-PSL), Paris, France tanay.katiyar20@gmail.com.
The Behavioral and brain sciences
|February 4, 2024
概括
研究地图需要高通量自然描述,以揭示设计空间的新见解. 这种系统的数据收集,虽然具有挑战性,但可以通过整合性实验设计解决方案来实现.
科学领域:
- 科学方法科学方法学
- 研究设计研究设计研究设计
- 数据科学是数据科学.
背景情况:
- 确定新的研究途径对于科学进步至关重要.
- 目前探索设计空间的方法范围有限.
- 了解"未知的未知"是创新的关键.
研究的目的:
- 提出高通量自然描述作为研究地图的方法.
- 解决系统收集和注释现实世界刺激的挑战.
- 概述解决方案,以克服数据采集中的后勤障碍.
主要方法:
- 系统地收集真实世界刺激的代表性体.
- 收集数据的注释,以便进行详细分析.
- 在实验设计框架中整合数据解决方案.
主要成果:
- 高通量自然描述可以识别"未知未知".
- 数据收集的后勤挑战是可以克服的.
- 解决方案的后期部署有助于整合性实验设计.
结论:
- 高通量自然描述对于有效的研究绘图是必不可少的.
- 通过战略实施,克服数据收集挑战是可行的.
- 这种方法将加强对复杂设计空间的探索.
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