Cauchy convergence analysis dashboard — semantic consistency, trajectory mapping, divergence matrices, and credibility scoring.
Fisher information measuring how much each successive statement reveals about a party's true position — distinguishing substantive communication from obfuscation in AI-assisted legal analysis.
KL divergence measuring how subsequent statements drift from a party's original position — asymmetric divergence detection for narrative anchor erosion in AI-assisted legal analysis.
Algorithmic complexity measuring narrative consistency through compressibility — honest accounts compress efficiently while deceptive ones resist compression in AI-assisted legal analysis.
Dynamical systems stability analysis applied to communication under pressure — measuring whether narratives remain in stable orbit or fly off trajectory when challenged in AI-assisted legal analysis.
MDL measuring the computational cost of explaining a party's narrative over time — contrived accounts require more complex models while good-faith explanations remain parsimonious in AI-assisted legal analysis.
Measuring how quickly statistical dependence between statements decays over time — consistent communicators maintain coherence while manipulators fragment into independent signals in AI-assisted legal analysis.
Information-theoretic analysis measuring thematic diffusion within single narratives and statistical coupling between parties — detecting strategic vagueness, coordinated messaging, and evidentiary disconnection in AI-assisted legal analysis.
Topological data analysis revealing structural shapes in communication — loops of circular reasoning, voids of avoided topics, and clusters of rehearsed talking points in AI-assisted legal analysis.
Earth Mover's Distance applied to communication analysis — measuring the minimum cost of transforming one semantic distribution into another to detect goalpost-moving and gradual narrative drift in AI-assisted legal analysis.