Symbol mu_H
m is part of the quantity the equation computes from the expression on the right.
Read this term in its guide →Published equation contexts
Suppose further that among the trait-positive horizontally exposed models, 70 percent produce a response diverging from the seeded canonical form beyond the declared threshold, =0.70 , against 15 percent for the vertically exposed group, =0.15 : horizontal transmission would be lossier, consistent with an indirect channel and with Mesoudi and Whiten’s finding that transmission-chain experiments on human cultural information typically show cumulative drift across successive links rather than the stable replication a simple copying model would predict [ 14 ] . And suppose a curation pass applied before the horizontally exposed artifact reached its downstream trainer moved the trait’s…
m is part of the quantity the equation computes from the expression on the right.
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Equation 52 · Evolutionary AI
This equation states an equality: the expressions on both sides have the same value under the article’s assumptions.
Suppose further that among the trait-positive horizontally exposed models, 70 percent produce a response diverging from the seeded canonical form beyond the declared threshold, =0.70 , against 15 percent for the vertically exposed group, =0.15 : horizontal transmission would be lossier, consistent with an indirect channel and with Mesoudi and Whiten’s finding that transmission-chain experiments on human cultural information typically show cumulative drift across successive links rather than the stable replication a simple copying model would predict [ 14 ] . And suppose a curation pass applied before the horizontally exposed artifact reached its downstream trainer moved the trait’s…
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