Read the equation
The example fixes N=1000 in the zero-reversion probability model. More checks tighten a probability bound only to the extent that their independence and common-probability assumptions are justified. One thousand adjacent correlated time samples are not automatically one thousand independent opportunities.
Terms & definitions
| Term | Meaning in this source |
|---|---|
| N | Number of checks |
How it works
Read the definition from its right-hand expression to the quantity on the left. Its surrounding source records the intended input, state, or parameter context. Where the source leaves an operation unspecified, this page preserves that gap.
Assumptions & limits
Source recovery establishes that the expression appears in this record. Its mathematical validity, implementation behavior, and interpretation must be assessed separately. See the linked source and research notes for the checks available for this version.
Original context
Read the surrounding source passage
Suppose no return to baseline is observed in N independent checks. Under a constant independent reversion probability p, Pzero reversions=1−pN. The one-sided 95% upper bound is 1−0.051/N. For N=1000, it is about 0.002991 per check. It is not zero. Dependence between checks makes this simple bound less informative, not a proof of eternity. A proof of permanent divergence is possible for a fully specified system when a forward-invariant set excludes the reference, as in the affine example. But that proves a property of those transition rules. A finite sequence of neural-model transcripts does not supply such a proof unless the required model and invariant are established independently. 10. A prospective study that would meaningfully test the proposal The following is a proposed protocol, not an executed experiment or a preregistration that has already been filed. Its purpose is to investigate the distinctive causal sequence without treating humanlike language as necessary and without defining success solely by the outcome it is meant to predict.
Exact original notation
N=1000