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Advancing Base Metal Catalysis through Data Science: Insight and Predictive Models for Ni-Catalyzed Borylation through Supervised Machine Learning
Research article (Organometallics, 2022) · cited 22× · AI/ML
Advancing Base Metal Catalysis through Data Science: Insight and Predictive Models for Ni-Catalyzed Borylation through Supervised Machine Learning
Summary
Advancing Base Metal Catalysis through Data Science: Insight and Predictive Models for Ni-Catalyzed Borylation through Supervised Machine Learning is a scholarly article[1].
Key Facts
Advancing Base Metal Catalysis through Data Science: Insight and Predictive Models for Ni-Catalyzed Borylation through Supervised Machine Learning's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Advancing Base Metal Catalysis through Data Science: Insight and Predictive Models for Ni-Catalyzed Borylation through Supervised Machine Learning. Retrieved May 24, 2026, from https://4ort.xyz/entity/advancing-base-metal-catalysis-through-data-science-insight-and-predictive-models-for-ni-catalyzed-borylation-through-su
MLA“Advancing Base Metal Catalysis through Data Science: Insight and Predictive Models for Ni-Catalyzed Borylation through Supervised Machine Learning.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/advancing-base-metal-catalysis-through-data-science-insight-and-predictive-models-for-ni-catalyzed-borylation-through-su.
BibTeX@misc{4ortxyz_advancing-base-metal-catalysis-through-data-science-insight-and-predictive-models-for-ni-catalyzed-borylation-through-su_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Advancing Base Metal Catalysis through Data Science: Insight and Predictive Models for Ni-Catalyzed Borylation through Supervised Machine Learning}}, year = {2026}, url = {https://4ort.xyz/entity/advancing-base-metal-catalysis-through-data-science-insight-and-predictive-models-for-ni-catalyzed-borylation-through-su}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Advancing Base Metal Catalysis through Data Science: Insight and Predictive Models for Ni-Catalyzed Borylation through Supervised Machine Learning — https://4ort.xyz/entity/advancing-base-metal-catalysis-through-data-science-insight-and-predictive-models-for-ni-catalyzed-borylation-through-su (retrieved 2026-05-24)
