Memory Evolutive Systems currently use externally parametrized dynamics rather than endogenous, self-referential time, so the approach remains outside the constitutive dynamic it describes.

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• Any system that persists must minimise surprisal, thereby gathering evidence for its own generative model, a process known as self-evidencing.claim0.802
  Foundational claim of the paper, defining self-evidencing.
• Memory is a candidate invariant that enables a Self to persist despite drastic alterations of substrate.claim0.770
  Memory transfer across tissues and through metamorphosis supports persistence of Self.
• The systematic behavioral shift of LLMs under self-referential processing conditions predicted by consciousness theories represents something more structured than superficial correlations in training dataclaim0.755
  The paper's claim that theoretical convergence across GWT, RPT, HOT, IIT makes the findings non-coincidental
• Self-evidencing is not only unimpaired but improved after emptiness realisation, as the pruned model is more parsimonious without loss of accuracyclaim0.754
  Addresses the concern that emptiness realisation might undermine adaptive functioning
• Evolutionary transitions in individuality constitute a form of deep model induction.claim0.754
  Links ETIs to the learning of hierarchical representations.
• Remapping memories onto a new body works because development is also regulative and able to remap genetic information into new scenarios.hypothesis0.751
  Core hypothesis linking developmental robustness to memory remapping.
• Evolutionary transitions in individuality correspond to deep interaction structures or perhaps other mechanisms of multi-scale dynamics.hypothesis0.750
  Concrete proposal about necessary architecture for ETIs.
• Evolution re-uses many of the same mechanisms and strategies across scales of organization and problem spaces.claim0.748
  Claims that scale-free dynamics, like bioelectric networks, are ancient and conserved.