A source claims to have been at an incident you are investigating. Before the call, you need a structured list of what a person actually present would know, ranked by what you can independently test.
The problem
A source has come forward. They were at the scene. They have details. The standard approach is to take the interview, transcribe it, and then verify against the public record after the fact. That approach is wrong in three ways. It rewards the source who tells a smooth story. It leaves the analyst running checks reactively against whatever the source happens to say. And it gives the source room to anchor the analyst's attention on the parts of the event they actually know, away from the parts where their account would fall apart.
The structured alternative is to build the verification checklist before the interview, not after. A person who was actually present has access to a specific bundle of signals: sensory details that match the public record, temporal details that align with documented timeline, environmental details that match imagery, and social details about other people present that can be cross-referenced. A person who was not present, or who was present at a different event and is conflating, will fail differently on each category.
The problem is that building this checklist from scratch for every incident is slow, and the analyst inevitably anchors on the categories they happen to think of first. The model can produce a complete checklist in seconds, ranked by independent verifiability, before the interview begins. That is the method this piece is about.
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