# Fresh external search notes — 2026-08-16

Fresh search was performed immediately before drafting EML-RKD-04.

All sources below are primary journal/conference/preprint sources or official scholarly indexes. They are used as methodological precedents, not as proof of the RKD framework.

## Sources

1. Samuel Recht, Ljubica Jovanovic, Pascal Mamassian, Tarryn Balsdon (2022), *Confidence at the limits of human nested cognition*, Neuroscience of Consciousness, niac014.
   - Demonstrates above-chance human second-, third-, and fourth-order nested judgments in a specific perceptual task.
   - Models recursive evidence degradation/noise and reports task dependence.
   - Relevant to separating structural recursion from functional quality.

2. Brian Maniscalco & Hakwan Lau (2014), *Measures of metacognition on signal-detection theoretic models*, Psychological Methods 19(2), 245–260, DOI 10.1037/a0033268.
   - Introduces meta-d' as a signal-detection-theoretic measure of metacognitive sensitivity that attempts to separate sensitivity from response bias.
   - Used as a measurement precedent, not as the canonical definition of RKD.

3. Richard Servajean & Philippe Servajean (2026), *Measuring the metacognition of AI*, arXiv:2603.29693.
   - Applies meta-d'/SDT style measurement to AI primary judgments, confidence, and risk-sensitive regulation.
   - Used as a cross-carrier measurement precedent.

4. Olivier Roy & Martin Vetterli (2007), *The Effective Rank: A Measure of Effective Dimensionality*, EUSIPCO 2007.
   - Defines effective rank using the entropy of normalized singular values.
   - Demonstrates that effective dimensionality can be real-valued even though ordinary rank is integer-valued.
   - Used specifically to show that a discrete rank gap is invariant-dependent.

5. Michael T. Cox et al. (2022), *Computational Metacognition*, arXiv:2201.12885.
   - Used as a non-human/artificial metacognitive architecture precedent.

## Search conclusion
The external literature supports the methodological need to distinguish:
- structural capacity,
- task-level sensitivity,
- noise/calibration,
- and measurement realization.

No external source establishes the RKD Dual-Gap Principle as a universal law; its statements in EML-RKD-04 are conditional consequences of the chosen algebraic/metric assumptions.