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data explorationGitHub
•87% Informative
Data-to-paper is an automation framework that systematically navigates interacting AI agents through a complete scientific research.
The process navigates through the entire scientific path, from data exploration, literature search and ideation, through data analysis and interpretation, to the step-by-step writing of a complete research paper.
The platform can run fully autonomously, or can be human-guided through the Copilot App .
The developers of this project do not accept responsibility or liability for any losses, damages, or other consequences that may occur as a result of using this software.
The process is NOT error-proof and human intervention is necessary to ensure accuracy and the quality of the results.
Data-to-paper manuscripts are watermarked for transparency as AI -created.
VR Score
89
Informative language
91
Neutral language
24
Article tone
formal
Language
English
Language complexity
68
Offensive language
not offensive
Hate speech
not hateful
Attention-grabbing headline
not detected
Known propaganda techniques
not detected
Time-value
long-living
External references
10
Source diversity
8
Affiliate links
no affiliate links