neural nations · CAMS/JUNO · Network Explorer

Institutional Weather

Where is the system under stress, where is it resilient, and what intervention would change the trajectory? An 8-node CAMS/JUNO coordination network, integrated live in your browser — pick a scenario, scrub through time, or nudge a node yourself and watch the rest of the system respond.

⚠ Bounded exploratory CAMS/JUNO dynamics — boundary-clamped to the valid 0–10 scale, but the interior dynamics are not calibrated against real institutional data. Treat trajectories as illustrative, not predictive.

Scenario

Layer

Trajectory

t = 0.0

Node colour = current layer value (darker/redder = higher). Edge thickness = coupling weight between nodes in this model's bond-topology matrix. Click a node to add it to the comparison panel →

Criticality ranking

Node comparison (click 2 nodes)

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Intervention

Δ Coherence

Δ Capacity

Δ Stress

Δ Abstraction

Export

Method note. Ports the fixed-and-stabilised cams_network_skeleton.py ODE engine to JavaScript (fixed-step RK4, dt=0.05): the canonical JUNO node-value formula V = C+K−S+0.5A on an 8-node × 4-metric (32-dimensional) system, with a general derivative clamp keeping every metric inside [0,10] regardless of the interior terms. The example bond-topology matrix and coefficients are unchanged from the Python skeleton and have not been calibrated against real institutional data — see the source skeleton for the documented stability history (three unbounded-growth bugs found and fixed) and known calibration gap (Capacity has no interior self-damping term; long trajectories can settle at a degenerate boundary equilibrium rather than an interpretable fixed point).