The phrase "automatically separated into" is correct and usable in written English.
It can be used when describing a process where something is divided or categorized without manual intervention.
Example: "The data was automatically separated into different categories based on the predefined criteria."
Alternatives: "instantly divided into" or "systematically categorized into".
Moreover, the co-activations were automatically separated into local and long-range ones, based on distance.
The VOIs were automatically separated into a trabecular and a cortical region.
Data for SBP and HR were analyzed by power spectral analysis, by which they were automatically separated into two frequency bands: a low frequency band (LF: 0.25 - 0.75 Hz) and a high frequency band (HF: 0.75 - 3.0 Hz) [ 12, 20].
The entire volume of interest was automatically separated into cortical and trabecular components, yielding average bone density (D100), trabecular bone density (Dtrab), meta-trabecular bone density (Dmeta), inner-trabecular bone density (Dinn), and cortical bone density (Dcomp) in milligrams HA/cc.
Remarkably, without any prior knowledge about the number of cell types in the samples, our algorithm automatically separated different cell types into different modules, with a few exceptions.
Once you've given it access to your Twitter account, Little Pork Chop enables you to draft out your thoughts and automatically separates them into new tweets based on the character count.
You can also automatically separate your friends into groups.
In addition, it employs a novel continuous gesture segmentation and recognition algorithm, which accurately and automatically separates hand movements into segments, and merges adjacent segments if needed, so that each gesture only exists in one segment.
It will automatically separate the track into instruments that could be customized.
The spherical system of vector functions can be applied to expand any vector as well as scalar function, and it further automatically separates the static deformation into two independent sub-problems: The LM-type and N-type.
In the second step a machine learning algorithm automatically separates the IC-fingerprints into six general classes after preliminary training performed on a small subset of expert-labeled components.
