{"results":[{"id":"derive-then-review","text":"Over-derive, then review catches errors, retraction cascades propagate corrections. Both roles overshoot (derive over-generates, review over-retracts). Working through candidate retractions is where insights hide","truth_value":"IN","justification_count":1,"dependent_count":3,"challenges":[],"last_reviewed":null,"review_result":null},{"id":"eem-epistemic","text":"Epistemic means not just facts but justified beliefs with truth values (IN/OUT), retraction cascades, contradiction records (nogoods), and derivation depth. This distinguishes EEM from RAG (which is external semantic memory but not epistemic)","truth_value":"IN","justification_count":0,"dependent_count":4,"challenges":[],"last_reviewed":null,"review_result":null},{"id":"eem-vs-rag","text":"RAG is external semantic memory but not epistemic. It retrieves content by similarity but has no justification chains, truth values, retraction cascades, or contradiction tracking. EEM adds the epistemic layer that RAG lacks","truth_value":"IN","justification_count":1,"dependent_count":0,"challenges":[],"last_reviewed":null,"review_result":null},{"id":"evidence-depth-ceiling","text":"Beliefs beyond depth 8 do not survive review. Retraction rate: 0% at depth 0, rising to 100% at depth 9+. The universal TMS is wide rather than deep","truth_value":"IN","justification_count":0,"dependent_count":1,"challenges":[],"last_reviewed":null,"review_result":null},{"id":"evidence-retraction-rate","text":"13-37% of derived beliefs are retracted per review round across multiple expert KBs. Self-correction works — the system finds and removes its own errors","truth_value":"IN","justification_count":0,"dependent_count":1,"challenges":[],"last_reviewed":null,"review_result":null},{"id":"retraction-cascade","text":"When a node goes OUT, all dependents whose justifications become invalid also go OUT — automatically, transitively. This is the most important operation: retract one belief and the network figures out what else falls","truth_value":"IN","justification_count":1,"dependent_count":0,"challenges":[],"last_reviewed":null,"review_result":null},{"id":"tms-doyle-1979","text":"Doyle (1979) designed Truth Maintenance Systems with SL justifications, propagation, retraction cascades, and an exogenous problem-solver slot. The TMS substrate is content-agnostic by design","truth_value":"IN","justification_count":0,"dependent_count":2,"challenges":[],"last_reviewed":null,"review_result":null}],"count":7,"limit":20,"offset":0}