Abstract: Systems, methods, and non-transitory computer readable media are provided for generating or obtaining situations in which scores indicative of a danger or a hazard exceeds a threshold, receiving a selection of a first situation, in response to receiving the selection of the first situation, obtaining intelligence data, asset data, and operational data, analyzing the intelligence data using a trained machine learning model for the first situation; and determining a response measure based on the analyzed intelligence data.

Abstract: In some examples, systems and methods for object pairings are provided. For example, a method includes: receiving an input associated with at least one of the one or more first values of one or more weights, the one or more weights corresponding to one or more model parameters associated with a task; determining one or more second values of the one or more weights, at least one second value of the one or more second values of the one or more weights being determined based at least in part on the input; modifying the machine-learning model based on the one or more second values of the one or more weights; determining a plurality of object pairings for the task by applying the modified machine-learning model to data associated with the task, each object pairing of the plurality of object pairings including an asset object and the target object.

Abstract: Systems, methods, and non-transitory computer readable media are provided for generating or obtaining situations in which scores indicative of a danger or a hazard exceeds a threshold, receiving a selection of a first situation, in response to receiving the selection of the first situation, obtaining intelligence data, asset data, and operational data, analyzing the intelligence data using a trained machine learning model for the first situation; and determining a response measure based on the analyzed intelligence data.

Abstract: A collaborative planning system facilitates sharing of critical plans (e.g., a military mission plan) within an organization and managing authorizations of the plans from reviewers at multiple levels within the organization. Once the plans are approved, a data object representative of the plans is created and stored in an ontology of data objects (with objects of various types and associations between related data objects) so that the plans may be identified as associated with related data objects via searches of the data objects in the ontology.