Experimental research tool. This tool applies a structural formula from Generative Geometry to climate and environmental systems. The same formula predicts drug combination response rates in oncology (24/35 published trials within 3 pts). Climate predictions are structurally derived, not empirically validated at the same level. Use as a thinking tool, not a policy recommendation.
Select system
Coming
Climate Intervention Predictor
Every climate system maintaining its current state is a dissipative system — it spends energy to resist change. The fossil fuel economy, tropical deforestation, car-centric transport, and biodiversity loss all maintain themselves through the same structural mechanisms: depth, temporal entrenchment, and coverage gaps.
This tool applies the same blockade formula used in the Drug Combination Response Predictor. No curve-fitting per system. No machine learning. One structural equation, calibrated against published evidence.
M = intervention potency · k = sub-phases covered · n = depth · τ = entrenchment · p = prior failed attempts · σ = cascade bonus
How it works: Select a climate system, choose an entrenchment stage, then pick 1–4 interventions. The formula computes the predicted effectiveness — the percentage reduction in the system's ability to maintain its current state.
The key insight: Coverage matters more than intensity. Two interventions targeting different sub-phases of the system's maintenance cycle produce exponentially higher blockade than two targeting the same sub-phase. This is the σ cascade — the same structural principle that makes immunotherapy + targeted therapy outperform two targeted therapies in oncology.
Predictions vs published evidence
Calibrated against published emission reduction data. Same formula, same structural principles as the oncology tool.
SYSTEM
SOURCE
OBSERVED
PREDICTED
GAP
Mean absolute error
Select a climate system from the left panel to start building intervention packages.
Where current policy has structural gaps
Every major climate policy leaves at least one sub-phase of the system's maintenance cycle uncovered. The formula identifies which gaps cost the most effectiveness.
EU Green Deal covers Signal (renewables, EVs) and Conservation (carbon pricing) but misses Encounter (feedback loops — no major CCS or nature-based sink programme). Predicted: adding reforestation would increase effectiveness by ~15 pts.
Paris Agreement covers Signal + Encounter + Conservation but misses Structure (structural lock-in — no infrastructure transition mandate). Adding regulation or subsidy reform closes the gap.
US IRA covers Signal + Structure + Encounter but misses Conservation (no carbon price signal). The σ cascade predicts this is the most costly gap — institutional coverage produces disproportionate returns.
Select a climate system from the left panel to explore intervention combinations.
The climate calibration (MAE ~8 pts across 8 evidence points) is less tight than the oncology calibration (MAE ~2 pts across 35 trials). Climate systems have fewer controlled experiments. We are working on:
Country-level parameters — Institutional quality, governance capacity, and enforcement credibility differ per country. A carbon tax in Sweden and one in Nigeria have the same sub-phase but different effective potency.
Transport as multiple systems — Transport is not one system. Road, aviation, shipping, and rail each run their own maintenance cycle. The current model treats urban road transport separately but the others need decomposition.
Expanding evidence — Adding country-level policy outcome data from the Science 2024 meta-analysis (1,500 policies, 41 countries) to calibrate M values against real measured emission reductions.
How to use
1 Select a climate system from the left
2 Choose an entrenchment stage
3 Pick interventions — or click a policy package to auto-fill