Title: AEEA 2026 Research Priorities: Planetary Orbits, Impact Risk, and Extinction Cycles
Subtitle: Reproducible science with falsifiable predictions, control models, and public-facing deliverables.
Who we are
AEEA is a nonprofit research initiative focused on long-horizon catastrophic-risk science. In 2026 we will prioritize three projects that are intuitive to the public, scientifically testable, and designed for independent replication.
Our engine (methods & tools)
Our 2026 work is enabled by MEST-AI and our structural-tensor modeling toolkit, consolidated as Mass–Energy–Spacetime Turning-Point Tensor Computation (MEST-TPC).
MEST-TPC is a computational method that parameterizes mass–energy–spacetime structural turning points via structural tensors and produces falsifiable predictions and parameter constraints through reproducible fitting and uncertainty quantification.
2026 Top-3 Projects (Public Value + Testability)
Impact Hazards: Evidence Index & Rate Modeling
Deliver: Impact Evidence Index v1, Impact Rate Model v1, uncertainty bounds, and a public summary report.
Why it matters: Converts “impact risk” into graded evidence and quantified uncertainty, enabling transparent risk communication.
Planetary Orbits: Testing Perturbations from Dark-Sector/Spacetime Hypotheses
Deliver: Orbit Test Protocol v1, Perturbation Constraints v1 (upper limits / parameter bounds), and a replication package.
Why it matters: Uses planetary orbits—an intuitive and measurable target—to test falsifiable perturbation predictions with controls.
Mass Extinction Periodicity: Statistical Robustness & Multi-Scale Coupling Tests
Deliver: Periodicity Robustness Report v1, Coupling Hypothesis Map v1, and control-model comparisons.
Why it matters: Separates signal from noise and avoids correlation-as-causation through explicit controls and sensitivity tests.
Our 2026 commitments
Falsifiability: Each project defines “what would disconfirm the hypothesis.”
Controls: Parallel models that do not require dark-sector mechanisms to avoid false causality.
Reproducibility: Public data indexing, versioned code, documented assumptions, and one-click figure generation.
Quarterly cadence: Visible progress every quarter (methods → results → controls → annual synthesis).
Call to action (sponsor options)
Sponsors enable open research outputs, external review, and reproducibility engineering.
Contact: AEEA Research Team — [email] — [website]
Tier 1 — USD 25,000 (Starter Sponsor)
Funds: One project v1 deliverable package (choose 1 of the 3 projects).
Includes: v1 report + replication package + sponsor acknowledgement.
Tier 2 — USD 100,000 (Core Sponsor)
Funds: Two projects delivered through the full annual cycle (v1→v2 improvements, controls, external review).
Includes: quarterly briefings + public release + external reviewer honoraria.
Tier 3 — USD 300,000 (Flagship Sponsor)
Funds: All three projects + annual synthesis (public + technical versions) + one open online seminar with invited reviewers.
Includes: full reproducibility engineering support and a formal “Methods & Controls” appendix for each deliverable.
Use of funds (typical allocation)
45% research labor (modeling, analysis, writing)
25% reproducibility engineering (pipelines, packaging, documentation)
15% external review & advisory honoraria
10% data acquisition/curation + computing
5% communications & publishing (public summaries, website updates)
Q1 (Jan–Mar): Foundations & Protocols
Impact: Evidence Index v1 (scoring rules + data source list)
Orbits: Orbit Test Protocol v1 (units, uncertainties, controls)
Periodicity: Robustness test plan + dataset registry
Q2 (Apr–Jun): First Results (v1)
Impact Rate Model v1 (uncertainty bounds + sensitivity tests)
Orbital perturbation constraints v1 (parameter bounds / upper limits)
Periodicity Robustness Report v1 (multi-method results + controls)
Q3 (Jul–Sep): Controls & Cross-validation
Cross-source validation and alternative-method replication
Control models fully documented and compared
Q4 (Oct–Dec): Annual Synthesis & Public Release
Annual report (public version + technical version)
Full replication package (versioned code + data index + one-click figures)
Research Engine (one-line)
Research Engine: MEST-AI powered by MEST-TPC, with reproducible pipelines, control models, and uncertainty bounds.
Scientific integrity
We publish negative results and failure boundaries.
We maintain explicit control models to prevent correlation-as-causation errors.
We welcome independent replication and reviewer feedback.
Biosecurity / safety
We do not conduct wet-lab work.
We do not publish experimental protocols or actionable methods that could increase biological harm capabilities.
Sponsor recognition & governance
Sponsors may support external review panels but do not influence scientific conclusions.
All outputs are versioned and publicly archived with reproducibility documentation.