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Article analysis:

The article provides a detailed overview of the use of the Augmented Kalman Filter (AKF) for predicting the full-field response of a structure, including unmeasured locations. The authors propose a methodology for automated process noise covariance adaptation, relying on response estimates recovered by means of an improved Modal Expansion approach and validate it using experimental data from a large scale research Wind Turbine blade made of glass fiber reinforced plastics.

The article appears to be reliable and trustworthy as it provides detailed information about the proposed methodology and its validation with experimental data. However, there are some potential biases that should be noted in order to ensure that readers have an accurate understanding of the article's content. For example, while the authors provide evidence for their claims regarding the efficacy of their proposed methodology, they do not explore any potential counterarguments or alternative approaches that could be used to achieve similar results. Additionally, while they note some possible risks associated with their approach, they do not provide any further details or discuss how these risks can be mitigated or avoided altogether. Furthermore, while they present both sides equally in terms of providing evidence for their claims and discussing potential risks associated with their approach, they do not explore any unexplored counterarguments or missing points of consideration that could potentially affect the accuracy and reliability of their results. Finally, there is no indication that promotional content has been included in the article which could potentially bias readers' opinions towards one side or another without providing sufficient evidence to support such claims.