The paper proposes the iSEEDs project to integrate machine learning with astrochemistry for extracting physical conditions and molecular abundances from protostellar disk datasets.
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2 Pith papers cite this work, alongside 487 external citations. Polarity classification is still indexing.
2
Pith papers citing it
487
external citations · OpenAlex
fields
astro-ph.SR 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
The paper reviews techniques for measuring protostellar accretion, analyzes methodological differences and caveats in comparing observations with simulations, and outlines next steps for a fuller picture.
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Astrochemical Study of Early Embedded Disks
The paper proposes the iSEEDs project to integrate machine learning with astrochemistry for extracting physical conditions and molecular abundances from protostellar disk datasets.
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The Accretion Process on Protostars
The paper reviews techniques for measuring protostellar accretion, analyzes methodological differences and caveats in comparing observations with simulations, and outlines next steps for a fuller picture.