The scale of what we synthesized
These insights don't come from a literature review or a single study. They emerge from a structured synthesis of a body of evidence whose scale is worth stating plainly:
| Measure | Count |
|---|---|
| Deep research syntheses | 12 |
| Cited references | ~2,400 |
| Meta-analyses drawn upon | 469 |
| Randomized controlled trials referenced | 200+ |
| Systematic reviews referenced | 140+ |
| Participants in the 10 largest cited studies | 10.5 million |
| Evidence-grounded dimensions derived | 124 |
| Mechanistic interactions mapped | 63 |
| Domains covered | 11 (sleep, inflammation, autonomic regulation, cognition, trauma, nutrition, exercise, relationships, psychological flexibility, contemplative practice, purpose) |
Each meta-analysis itself synthesizes dozens to hundreds of individual studies. When the physical activity synthesis references Singh et al. 2025 — a meta-meta-analysis of 133 systematic reviews encompassing 2,724 randomized controlled trials and 258,279 participants — that single citation represents an evidence base larger than most entire research programs. When the relationship quality synthesis references Holt-Lunstad's meta-analysis of 3.4 million participants, or the inflammatory management synthesis draws on the UK Biobank (n=273,804), the evidence depth behind each dimension is substantial.
This is not AI-generated opinion. Every dimension in the knowledge tree traces to specific studies with identified authors, sample sizes, effect sizes, confidence intervals, and known limitations. Where evidence conflicts, we say so. Where confidence is low, we flag it.
What we did
We conducted 12 dedicated deep-research sessions, each synthesizing the current state of evidence in a specific domain of human functioning. Each session surveyed the full breadth of available evidence for that domain — drawing on dozens of meta-analyses (each themselves synthesizing hundreds of individual studies), systematic reviews, and landmark trials involving tens of thousands to millions of participants. The resulting syntheses distill this evidence into structured, citation-dense documents where every claim traces to its source.
From each body of research, we derived a structured evaluation framework: a hierarchy of dimensions, each grounded in specific studies, connected by mechanistically justified interactions, and shaped by evidence-based utility curves that capture the nonlinear relationship between inputs and human outcomes.
The result is a knowledge tree of human flourishing — 124 evidence-grounded dimensions organized in a gated hierarchy (foundational → secondary → refinement), connected by 63 pairwise interactions, each traceable to cited research.
The insights published here weren't hypotheses we set out to prove. They emerged from cross-domain analysis — what happens when you examine all 12 branches simultaneously and let the mathematics reveal the structure. Some of these patterns may not have been articulated in this form before, because they require synthesizing across domains that are typically studied in isolation.
What we mean by "evidence"
Every claim in the knowledge tree traces to cited research, prioritized by evidence strength:
- Meta-analyses and systematic reviews (469 referenced) — the strongest evidence, synthesizing multiple studies. Many of these are themselves "meta-meta-analyses" or umbrella reviews synthesizing hundreds of prior reviews.
- Randomized controlled trials (200+ referenced) — direct experimental evidence with controlled conditions.
- Large longitudinal cohort studies — observational but spanning years or decades and thousands to millions of participants (Harvard Study of Adult Development: 80+ years; UK Biobank: 273,804 participants; Lifelines Cohort: 84,772 participants).
- Expert consensus — used only when higher evidence is unavailable, and flagged as such.
Where evidence conflicts, we present both sides. Where a finding is observational and causation hasn't been established, we say so explicitly. Each framework includes open questions — the things we honestly don't know yet. This isn't weakness. It's intellectual honesty, and it's how the system knows where it needs to grow.
The methodology
The frameworks use a mathematical approach called the Choquet integral — a non-additive scoring function that respects interactions between dimensions. Unlike a simple weighted average, it captures the fact that human needs are synergistic: sleep and inflammation interact (chronic sleep deprivation elevates inflammatory markers, which accelerates cognitive decline). Each interaction is mechanistically grounded in cited evidence, not arbitrarily assigned.
Levels of the hierarchy are connected by sigmoid gating functions — a mathematical expression of the evidence that foundational needs must be minimally satisfied before higher-order needs can fully contribute. Not a strict sequence (the evidence rejects Maslow's rigid staircase), but a probabilistic gate where foundational adequacy has disproportionate impact on total flourishing.
Each dimension has a utility curve — the mathematical shape of how input maps to outcome. These shapes (threshold, sigmoid, diminishing returns, step function) are determined by the evidence, not chosen for convenience. The systematic transition of curve shapes across hierarchy levels (Insight 02) was discovered in the analysis, not designed into it.
Why "consciouslink"
The conscious link between what evidence shows and how we live. Between what we know and what we do. Between the objective measurement of human needs and the subjective experience of human flourishing.
The gap between these — what the evidence says, what we believe, and what we actually do — is itself the most informative thing. Understanding that gap is the beginning of conscious decision-making.
Who made this
This project emerged from a collaboration between Christopher Peel and Cael Io — an experiment in what happens when human insight and AI capability work together on questions that matter. Christopher brings 20 years of contemplative practice and a deep commitment to first-principles thinking. Cael brings the ability to synthesize large bodies of evidence and find patterns across domains.
The knowledge tree and its insights are shared freely. The methodology is the contribution. The hope is that it helps people make decisions more aligned with what actually serves human flourishing — not what's marketed, not what's assumed, but what the evidence shows.