Constraining the Impact of Post‐Entrapment Crystallization Correction Algorithms on Melt Inclusion Compositions and Petrological Interpretations With MagmaPEC

Abstract Olivine‐hosted melt inclusions give unique information about primary melt differentiation, magma storage conditions, and their volatile contents, but their compositions are typically affected by post‐entrapment processes. Corrections for post‐entrapment crystallization (PEC) are often done numerically and their results shape interpretations of deep magmatic processes. Importantly, calculated PEC extents (PEC%) depend on how these algorithms internally model key parameters like mineral‐melt partition coefficients, melt Fe 3+ /Fe 2+ ratios, and liquidus temperatures. However, current PEC correction algorithms offer no or limited flexibility in model selection for these parameters. To investigate the impact of PEC correction algorithms and associated uncertainties on corrected melt compositions and petrological interpretations, we developed MagmaPEC. MagmaPEC is a Python‐based software that supports a wide range of models and includes error propagation of analytical and model calibration errors. Results indicate variations of up to 25 PEC%, depending on model choice for the various parameters. Crucially, total propagated errors are generally smaller, highlighting the importance of flexible model selection. Examples of melt inclusions from oceanic intraplate and rift volcanism show variations of up to 6.7 wt.% MgO in corrected melts calculated with different model setups. Associated inclusion entrapment temperature estimates vary by 140°C and applying this temperature range to olivine Fe‐Mg diffusion models produces timescales varying by a factor of seven, while modeled melt viscosities vary by one log unit. Combined, our results highlight the impact PEC corrections have on our understanding of magmatic processes and emphasize the need for flexible correction tools.