Claims › ext:1d68a588bb653191 › line of work
Its line of work
Two new sequence datasets (CB513 and CB251) are derived which are suitable for cross-validation of secondary structure prediction methods without artifacts due to internal homology.
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.
● established◐ supported○ unchecked◆ contested✕ refuted⊘ tried, not checkable
human literature published here declared by its author identified in the literature refutesleft to right: what rests on what
size: stakes, by area; the largest here 8.5 the claim it is drawn around
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Every claim drawn, as a table
| Claim | Status | Checkable | Credence | Use | Stakes | Rests on |
|---|---|---|---|---|---|---|
| The performance of the model surpasses current state-of-the-art unsupervised structure learning methods by a wide margi… | ○ unchecked | yes | 0.55 | 0 | 8.5 | Two new sequence datasets (CB513 and CB251) are derived which are suitable for cross-validation of secondary structure… |
| Two new sequence datasets (CB513 and CB251) are derived which are suitable for cross-validation of secondary structure… | ○ unchecked | yes | 0.55 | 0 | 1.0 | — |
| We find that self-supervised pretraining is helpful for almost all models on all tasks, more than doubling performance… | ○ unchecked | yes | 0.55 | 0 | 0.0 | Two new sequence datasets (CB513 and CB251) are derived which are suitable for cross-validation of secondary structure… |
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Step by step
| Where | Status | Claim | Credence |
|---|---|---|---|
| this claim | unchecked | Two new sequence datasets (CB513 and CB251) are derived which are suitable for cross-validation of secondary structure prediction methods without artifacts due…human literature · ext:1d68a588bb653191 | 0.55 |
| 1 step above | unchecked | The performance of the model surpasses current state-of-the-art unsupervised structure learning methods by a wide margin, with far greater parameter efficiency…takes its method from this claim, as the citing paper says · human literature · ext:180f20b5b824c56e | 0.55 |
| 1 step above | unchecked | We find that self-supervised pretraining is helpful for almost all models on all tasks, more than doubling performance in some cases.replicates this claim, as the citing paper says · human literature · ext:887c6102a4f6d766 | 0.55 |
Background mentions carry no weight and are not part of the line. Every number recomputes from the public log.