#geochemistry

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Eugene @datastory@mstdn.ca · Jul 08, 2026
🌎 Why 1960s Geoscience Classics Still Matter in Data Science Data without domain expertise is noise. It’s easy to get caught up in R or ML, but foundational science drives true insight. I'm revisiting N.M. Strakhov's masterpiece "Principles of Lithogenesis" (1960-62, translated 1967). Springer’s 2014 digital reprint (Google Books) proves its value. Over 60 years later, his systematic approach to sedimentary environments and geochemistry remains highly relevant. ❓ Why this matters for spatial analytics: 🔹 Ground-Truthing: You can't model watershed contamination, mine waters, or deposits via desktop sowtware alone if you ignore baseline lithological and geochemical laws. 🔹 Feature Engineering: The best domain features come from understanding physical processes—like how basins and geochemical barriers function. ❗ Tools change, but physical laws are timeless. Understanding both turns raw data into actionable insights. #Geology #Geochemistry #DataScience #SpatialAnalysis #Springer #GoogleBooks #Lithogenesis
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Dr. Or M. Bialik @ombialik@mastodon.world · Jul 03, 2026
#WeekendReading: Remírez et al., about a boron-based salinity proxy for normal marine conditions! I'm going for cautiously optimistic. Link: https://www.sciencedirect.com/science/article/pii/S0009254126003505 #Boron #Paleosalinity #Proxy #Geochemistry
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