Extracting structured data from organic synthesis procedures using a fine-tuned large language model
The popularity of data-driven approaches and machine learning (ML) techniques in the field of organic chemistry and its various subfields has increased the value of structured reaction data. Most data in chemistry is represented by unstructured text, and despite the vastness of the organic chemistry...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Royal Society of Chemistry
2024
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| Online Access: | https://hdl.handle.net/1721.1/157469 |