Provenance integrity
Where a claim came from, who published it, and whether the chain from origin to publication survives inspection: authorship, citation, content credentials, edit history and attribution of images, quotes and data.
Challenge
Misinformation Challenge (MIS)
A global cognitive challenge — where coherence fails before truth does.
Misinformation rarely arrives as an outright lie. It arrives as framing, omission, drift, and amplification — small distortions that break the coherence between a claim, its evidence, and the words used to carry it.
Challenge MIS reads misinformation as a multi-layered failure of integrity, not a single failure of truth.
Evidence integrity
Whether the claim is supported by verifiable evidence: data, documents, primary reporting, reproducible measurement, and the distance between what is asserted and what is demonstrated.
Manipulation detection
Deliberate distortion: fabricated content, synthetic media, deceptive framing, decontextualised material, coordinated inauthentic behaviour and impersonation of trusted institutions.
Amplification dynamics
How a claim travels: recommender exposure, virality, echo-chamber concentration, cross-platform propagation and the speed at which a correction can catch up with the original.
Societal resilience
Capacity to withstand distortion: media literacy, plural and funded journalism, institutional trust, transparent correction practice and democratic oversight of information infrastructure.
Cognitive Gaming
Three analysis modes — Cohesion, Truthfulness, Quantification — turn evaluation into a playable sequence of choices instead of a passive read.
Play the modes →Hexagonal Cognition Engine
Six-direction semantic analysis: each edge and apex carries a thinking direction, so a claim is examined from analytical and conceptual angles alike.
Explore the hexagon →Categorised 3D Vocabulary
Structured meaning — tags placed in a hierarchy of domain, scope, and rod — so wording differences become measurable rather than anecdotal.
See the vocabulary →Machine Validation Modules
Eight dimensions of machine credibility: factuality, calibration, provenance, bias, robustness, consistency, coverage, and stability.
View modules →Agentic Validation APIs
Traceability, reproducibility, and alignment: every score carries the source, the method, and the run that produced it.
View validation →