Let q be the probability of copying one base correctly and L the strand length. If errors are independent and every position has the same correctness probability, the probability of an exact copy is qL. This is ordinary repeated multiplication, not a reconstruction of an early replicator.
Exact sequence identity is not the same as useful function. Some changes leave activity intact, some destroy it, and some improve it in a particular environment. An evolutionary model also needs relative reproduction rates, population sizes, resources, and the effects of mutations. The exact-copy calculation alone does not establish a universal maximum genome length.
Suppose two RNA variants differ in their ability to help copying. If the more effective variant leaves more descendants and its sequence is inherited, the population can change by natural selection. If all molecules make random new sequences unrelated to their templates, better performance is not reliably passed on.
A catalyst that helps every nearby template equally raises another problem. A shorter or nonfunctional template might copy faster while benefiting from the useful catalyst. Such parasitic templates can undermine a shared copying system. Compartments can sometimes limit this sharing, but introduce their own costs.
Derive the exact-copy probability before interpreting it
Begin with a two-position example rather than a long strand. Suppose each position is correct with probability ninety percent, independently of the other. Both positions are correct with probability 0.9 times 0.9, or 0.81. Exactly one error has probability 0.9 times 0.1 plus 0.1 times 0.9, or 0.18. Two errors have probability 0.1 times 0.1, or 0.01. These three mutually exclusive outcomes sum to one.
For an exact copy of a longer strand, every position must be correct. Under the same independence and equal-correctness assumptions, multiply the per-position probability once for each position. That repeated product is q raised to L. Here q is a probability between zero and one, not the percentage number ninety-nine. For ninety-nine percent correctness, use 0.99 rather than 99 in the multiplication.
Select the one-error-per-hundred-bases preset. The twenty-base panel gives about 81.8 percent exact copies, while the hundred-base panel gives about 36.6 percent. One error on average per hundred positions does not mean that every hundred-base product has exactly one error. Some have none, some have one, and some have more. The average number of errors and the probability of having zero errors are different summaries of a distribution.
Then select Higher fidelity. At 99.9 percent per position, the hundred-base exact-copy fraction is about 90.5 percent. Small improvements per position can matter across many positions because each multiplication compounds the effect. At the Frequent errors preset, the hundred-base fraction is below 0.1 percent, not zero. The interface uses a threshold label so a small positive probability is not mistaken for impossibility.
The model is conditional on its simplified copying assumptions. It does not calculate the probability that copying starts, reaches full length, separates from its template, or produces a functional catalyst. For a separate invented calculation, suppose half of attempted products reach full length and 36.6 percent of those completed products are exact. Then about 18.3 percent of all attempts produce exact full-length copies. The completion fraction is an additional assumption, not an output of the slider.
Exactness is also different from function. A changed base might preserve a useful fold, disrupt it, or alter its activity under particular conditions. You cannot infer the proportion of functional products from q raised to L without information about which changes matter. Nor does an exact copy necessarily function if its environment prevents folding or destroys it before it acts. Sequence measurements and activity measurements answer different questions.
Real errors need not be independent or equally likely at every position. Neighboring sequence, particular base pairs, and reaction conditions can change error behavior. The calculation isolates one consequence of accumulated copying risk; it does not establish a universal genome-size limit or a complete evolutionary error threshold. To make an evolutionary prediction, you would also need how variants reproduce, survive, compete for resources, and pass their differences to descendants.