Phoebe's Neuro-Edge is peer-reviewed.
The aggregation, calibration, and deliberation mechanics that power the Intelligence Engine sit on a foundation of published cognitive science from CSO Bahador Bahrami and collaborators.
Calibrated certainty over binary signal
Every prediction is graded on conviction. Forecasters who say 90% must be right 90% of the time — calibration becomes part of merit weighting.
Structured deliberation over unstructured crowds
Phoebe enforces blind and semi-blind phases inside social circles. Forecasters commit before peers reveal — neutralising bandwagon contagion.
Merit weighting over equal voice
Historical accuracy, calibration quality, and argument density compound into a per-forecaster weight applied to each contribution.
Atomic arguments over opaque scores
Every aggregated forecast is reconstructible from its atomic arguments — making Phoebe's outputs auditable in a way market scores never are.
Aggregated knowledge from a small number of debates outperforms the wisdom of large crowds.
A core finding underwriting Phoebe: small, structured debates aggregated to consensus systematically outperform large unstructured crowds. The cognitive bandwidth of deliberation beats the raw sample size of polling.
Democratic forecast: Small groups predict the future better than individuals and crowds.
Replicates and extends the small-group advantage across forecast horizons: aggregated micro-deliberations beat both lone experts and unstructured crowds. The basis for Phoebe's circle topology.