When encountering inferred rows in Caboodle, what primary key values do they have?

Inferred rows in Caboodle are generated from relationships and logic rather than direct input, which means they do not correspond to actual entries in the source data that would typically have been recorded. These inferred rows are often used to represent hypothetical scenarios or deduced facts based on existing data patterns.

The primary key values assigned to inferred rows are non-negative. This can be understood from the design principles of the Caboodle Data Model, which aims to maintain consistency and clarity in data representation. By using non-negative values for primary keys, the model avoids ambiguity and ensures that these identifiers can be easily managed within the database, avoiding complications that could arise from negative key values.

When managing the data within a system like Caboodle, it is important to have a clear framework for how records are identified. Non-negative primary key values simplify the identification and retrieval process, particularly when it comes to querying and joining datasets.

Inferred rows are distinct from regular rows because they do not need to be strictly tied to the primary data sources; rather, they serve as extensions or logical conclusions from existing data. Therefore, the decision to assign non-negative values to these keys supports operational integrity and ensures that the data remains manageable and interpretable within the broader caboodle framework.