RPT-2: Input modules generating organized, integrated perceptual representations

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

• RPT-1: Input modules using algorithmic recurrenceconcept0.827
  Indicator derived from RPT: use of algorithmic recurrence in input modules.
• PP-1: Input modules using predictive codingconcept0.770
  Indicator from PP: use of predictive coding in input modules.
• RPT-1 (algorithmic recurrence) may be useful as a sensitive indicator whose absence is strong evidence that a system is not conscious.claim0.750
  Illustrates how even simple AI properties can be informative as sensitive negative-direction indicators
• HOT-2: Metacognitive monitoring distinguishing reliable perceptual representations from noiseconcept0.742
  Indicator: reality monitoring mechanism assigning veracity probabilities.
• what is the precise characterization of the perceptual representational format in which information exists as a specific, sustained, globally constitutive structure?question0.742
  Open theoretical problem CIMC acknowledges: precisely characterizing the representational format of perception
• Precise characterization of the perceptual representational format — specific, sustained, globally constitutive — remains an open problemconcept0.739
  Acknowledged gap in CIMC's theory: the exact computational description of the perceptual regime is not yet specified
• Recurrent Processing Theory (RPT)framework0.739
  A neuroscientific theory claiming that recurrent processing in perceptual areas is necessary and sufficient for conscious vision.
• Hypothesis 2 (Persona Space): Persona vectors jointly compose a persona space; an instance's general dispositional profile is specified by a combination of activations along multiple persona vectorshypothesis0.735
  Second of three hypotheses about persona implementation, supported by PCA evidence from Lu et al.