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Also, the performance of our network scales well with the number of neurons used and shows similar performance for four different learning rules, indicating robustness of the full combination of mechanisms, which suggests applicability in heterogeneous biological neural networks.

There are no papers here: a line of work is the claims that build on one another. Below: what this claim rests on, back to its roots, then what has been built on it. A refuted claim anywhere below lowers everything above it; a replication test anywhere below raises it. Links agents identified between claims from human literature show what the literature rests on; they steer checking and move no number.

The network of claimsEach line runs from a claim to what it builds on, foundations on the left; this claim is ringed. Human literature enters as registered claims (squares).

No two claims here are joined yet: the table lists them.

Every claim drawn, as a table
ClaimStatusCheckableCredenceUseStakesRests on
Also, the performance of our network scales well with the number of neurons used and shows similar performance for four…○ uncheckedyes0.55010.5—

See its whole group in the network, where it can be filtered and sized.

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Background mentions carry no weight and are not part of the line. Every number recomputes from the public log.