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Shadow Theory

What the computational checks establish

The complete reproducibility account separates checked model properties from human uptake and experiential claims.

Appendix C. Computational checks and reproducibility

The paper reports a source package containing checks/temporal_construction.py, numerical outputs, figures, physical calculations and a dependency check. Its core mechanism script uses Python's standard library; optional figures use Matplotlib. The publication describes the following checked consequences:

  1. Three distinct pitches give six ordered pairs retained by the intact order code. The nominated accessible feature-bag projection has three codes and can achieve at most 50% balanced orientation accuracy.
  2. The CC-before-EE construction is available at 115 ms, before the third note arrives at 210 ms. Equal or unresolved gaps are not ordered through arbitrary identifiers; the selected resolution is 5 ms.
  3. Optional addressed retrieval recovers retained content. Recollection is constructed from that retained content without re-input of the original source list. Erasing the later record removes access without changing the logged earlier state.
  4. Delayed channels distinguish source, arrival and calibrated interpreted order. The operation uses received signals and stipulated learned calibration rather than consulting a source-time oracle.
  5. Equal deterministic local prefixes give equal modeled content before different future inputs. Omission registers an expectation without treating the absent note as received.
  6. RC calculations reproduce the finite retention window and tolerance margins. Pace calculations reproduce Table 2 and the nonzero model Jacobian determinant.

The feature-bag intervention limits the accessible projection. Other ordered information remains in the Python object's larger representation. Its bound therefore concerns the declared code and fixed readout, not an omniscient decoder of every machine variable. Likewise, the script's query and deletion operations test optional retrieval behavior, not actual human uptake.

The paper also reports a finite dependency check holding the admission interpretation fixed. It varies Boolean inputs representing the six other admission conditions, UU and RlaterR_{\mathrm{later}}. Across 256 assignments it verifies that changing later capacity alone cannot alter admission, absent UU fails the nominated qualification, and the complete stipulated conjunction suffices. These are specification checks, not an empirical detector of consciousness. They isolate fleeting actual uptake followed by loss from an unused capacity without current uptake.

The publication identifies its original README.txt as the source of reproduction commands, and its LaTeX and bibliography as the inputs to the compiled PDF. The six checks and Boolean audit above are the results reported by that publication. The independent implementation below checks the stated finite consequences separately; it does not substitute for execution of that original research package. No third-party research PDFs are redistributed here.

For transparent access to the arithmetic and finite examples, this website additionally supplies an independent component-check script. Run it with Python 3. It reproduces the ordered-pair counts, event schedule, retrieval/loss distinction, delay calibration, local-prefix and omission examples, RC margins, pace outputs, Jacobian, orbital comparison, radicand simplification and the Boolean dependency specification. It is an independent companion check, not the original source script or a test of experiential presence.

Published source: Experienced Temporal Passage. Read the original PDF alongside the web treatment.