Samples with the highest solubility after high-throughput screening.

<p>Samples with the highest solubility after high-throughput screening.</p>

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Bibliographic Details
Main Author:	Bin Pan (742525) (author)
Other Authors:	Xiaoyu Hou (1571344) (author), Mingxin Zhang (4898947) (author), Jingxian Yu (1332696) (author), Conghui Zhang (3456536) (author), Yunhui Zhang (65111) (author), Xiaolong Su (2015140) (author), Shuangcai Li (16458999) (author)
Published:	2025
Subjects:	Genetics Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified prediction results indicate mean absolute error essential physical property generalizable prediction model stackboost model excels stackboost model decreases successfully identified compounds div >< p predicting aqueous solubility stackboost model model ’ aqueous solubility xgboost ), water solubility transfer learning throughput screening systematically compares significantly outperforming scale datasets rf ). random forest organic compounds material resources high potential generalization ability five well different datasets determination () conducted high comparative models adaptive boosting
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