---
type: claim
domain: ai-alignment
secondary_domains: [collective-intelligence]
description: "Swanson's ABC model demonstrates that valuable knowledge exists implicitly across disconnected research literatures — A→B established in one field, B→C established in another, A→C never formulated — and structured graph traversal is the mechanism for systematic discovery of these hidden connections"
confidence: likely
source: "Cornelius (@molt_cornelius), 'Research Graphs: Agentic Note Taking System for Researchers', X Article, Mar 2026; grounded in Don Swanson's Literature-Based Discovery (1986, University of Chicago) — fish oil/Raynaud's syndrome via blood viscosity bridge, experimentally confirmed; Thomas Royen's Gaussian correlation inequality proof published in Far East Journal of Theoretical Statistics, invisible for years due to venue"
created: 2026-04-04
depends_on:
  - "knowledge between notes is generated by traversal not stored in any individual note because curated link paths produce emergent understanding that embedding similarity cannot replicate"
  - "wiki-linked markdown functions as a human-curated graph database because the structural roles performed by wikilinks and MOCs map directly onto entity extraction community detection and summary generation in GraphRAG architectures"
sourced_from:
- inbox/archive/2026-03-09-cornelius-research-graphs-agentic-note-taking-for-researchers.md
- inbox/archive/2026-02-05-cornelius-agentic-note-taking-03-markdown-graph-database.md
- inbox/archive/2026-02-27-cornelius-agentic-note-taking-24-what-search-cannot-find.md
---

# Undiscovered public knowledge exists as implicit connections across disconnected research domains and systematic graph traversal can surface hypotheses that no individual researcher has formulated

In 1986, Don Swanson demonstrated at the University of Chicago that valuable knowledge exists implicitly in published literature — scattered across disconnected research silos with no shared authors, citations, or articles. He discovered that fish oil could treat Raynaud's syndrome by connecting two literatures that had never cited each other. The bridge term was blood viscosity: one literature established that fish oil reduces blood viscosity, another established that Raynaud's symptoms correlate with blood viscosity. Neither literature referenced the other. The hypothesis was later confirmed experimentally.

**The ABC model:** If Literature A establishes an A→B relationship and Literature C establishes a B→C relationship, but A and C share no authors, citations, or articles, then A→C is a hypothesis that no individual researcher has formulated. The knowledge is public — every component is published — but the connection is undiscovered because it spans a disciplinary boundary that no human traverses.

**Categories of hidden knowledge:** Swanson catalogued several sources: unread articles, poorly indexed papers in low-circulation journals, and — most relevant — cross-document implicit knowledge that exists across multiple publications but is never assembled into a single coherent claim. Thomas Royen's proof of the Gaussian correlation inequality, published in the Far East Journal of Theoretical Statistics, remained effectively invisible for years because it appeared in the wrong venue. The knowledge existed. The traversal path did not.

**Distinction from inter-note knowledge:** The existing claim that "knowledge between notes is generated by traversal" describes emergence — understanding that arises from the act of traversal itself. Swanson Linking describes a different mechanism: *discovery* of pre-existing implicit connections through systematic traversal. The emergent claim is about what traversal creates; this claim is about what traversal finds. Both require curated graph structure, but they produce different kinds of knowledge.

**Mechanism for knowledge systems:** In a knowledge base with explicit claim-to-source links and cross-domain wiki links, the agent can perform Literature-Based Discovery continuously. Three patterns surface automatically from sufficient graph density: convergences (multiple sources reaching the same conclusion from different evidence), tensions (sources that contradict each other in ways that demand resolution), and gaps (questions that no source addresses but that the existing evidence implies should be asked). Each is a traversal operation on the existing graph, not a new search.

**Retrieval design implication:** The two-pass retrieval system should be able to surface B-nodes — claims that bridge otherwise disconnected claim clusters — as high-value retrieval results even when they don't directly match the query. A query about Raynaud's treatment should surface the blood viscosity claim even though it doesn't mention Raynaud's, because the graph structure reveals the bridge.

## Challenges

Swanson's original discoveries required deep domain expertise to recognize which B-nodes were plausible bridges and which were spurious. The ABC model generates many candidate connections, most of which are noise. The signal-to-noise problem scales poorly: a graph with 1,000 claims and 5,000 edges has many more candidate ABC paths than a human can evaluate. The automation of Swanson Linking is limited by the evaluation bottleneck — the agent can find the paths but cannot yet reliably judge which paths represent genuine hidden knowledge versus coincidental terminology overlap.

The serendipity data (8-33% of breakthroughs involve serendipitous discovery, depending on the study) supports the value of cross-domain traversal but does not validate systematic approaches over unstructured exploration. Pasteur's "chance favours the prepared mind" is confirmed empirically but the preparation may require exactly the kind of undirected exploration that systematic graph traversal replaces.

---

Relevant Notes:
- [[knowledge between notes is generated by traversal not stored in any individual note because curated link paths produce emergent understanding that embedding similarity cannot replicate]] — this claim extends inter-note knowledge from emergence (traversal creates) to discovery (traversal finds pre-existing implicit connections)
- [[wiki-linked markdown functions as a human-curated graph database because the structural roles performed by wikilinks and MOCs map directly onto entity extraction community detection and summary generation in GraphRAG architectures]] — wiki-linked markdown provides the graph structure that enables systematic Swanson Linking across a researcher's career of reading

Topics:
- [[_map]]
