Claims › ext:684d52921617b203 › line of work
Its line of work
Readily programmable through modern software libraries, we show that a standard feed-forward neural network can be trained to detect multiple types of order parameter directly from raw state configurations sampled with Monte Carlo.
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.
No two claims here are joined yet: the table lists them.
Every claim drawn, as a table
| Claim | Status | Checkable | Credence | Use | Stakes | Rests on |
|---|---|---|---|---|---|---|
| Readily programmable through modern software libraries, we show that a standard feed-forward neural network can be trai… | ○ unchecked | yes | 0.55 | 0 | 10.5 | — |
See its whole group in the network, where it can be filtered and sized.
Step by step
| Where | Status | Claim | Credence |
|---|---|---|---|
| this claim | unchecked | Readily programmable through modern software libraries, we show that a standard feed-forward neural network can be trained to detect multiple types of order pa…human literature · ext:684d52921617b203 | 0.55 |
Background mentions carry no weight and are not part of the line. Every number recomputes from the public log.