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Data of "Chemistrees: Data-Driven Identification of Reaction Pathways via Machine Learning"

<p>This is the data and assosiated in-house code for the paper:</p> <p>Chemistrees: Data-Driven Identification of Reaction Pathways via Machine Learning</p> <p>Sander Roet, Christopher D. Daub, and Enrico Riccardi</p> <p>Journal of Chemical Theory and Computation <strong>2021</strong> <em>17</em> (10), 6193-6202</p> <p>DOI: 10.1021/acs.jctc.1c00458</p>

ShareScore

28/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
0
Engagement
0

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