Claims › ext:1a15ce17804bcaa3 › line of work

Its line of work

Critically, EvoDiff can generate proteins inaccessible to structure-based models, such as those with disordered regions, while maintaining the ability to design scaffolds for functional structural motifs.

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).

● 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 13.2 the claim it is drawn around

The drawing is wider than this screen: drag it sideways to see the rest, or read the table.

Every claim drawn, as a table

Claim	Status	Checkable	Credence	Stakes	Rests on
Critically, EvoDiff can generate proteins inaccessible to structure-based models, such as those with disordered regions…	○ unchecked	yes	0.55	7.3	Using a new combination of a protein language model that allows us to make predictions from single sequences and a geom…, We validated the advantage of using the embeddings as exclusive input for several subsequent tasks: (1) a per-residue (…, Dimensionality reduction revealed that the raw pLM-embeddings from unlabeled data captured some biophysical features of…
Using a new combination of a protein language model that allows us to make predictions from single sequences and a geom…	○ unchecked	yes	0.55	10.3	—
We validated the advantage of using the embeddings as exclusive input for several subsequent tasks: (1) a per-residue (…	○ unchecked	yes	0.55	13.2	—
Dimensionality reduction revealed that the raw pLM-embeddings from unlabeled data captured some biophysical features of…	○ unchecked	yes	0.55	12.2	—

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

Step by step

Where	Status	Claim	Credence
1 step below	unchecked	Using a new combination of a protein language model that allows us to make predictions from single sequences and a geometry-inspired transformer model trained…this claim takes its method from it, as the citing paper says · human literature · ext:6227586b2261cdb9	0.55
1 step below	unchecked	We validated the advantage of using the embeddings as exclusive input for several subsequent tasks: (1) a per-residue (per-token) prediction of protein seconda…this claim takes its method from it, as the citing paper says · human literature · ext:9be3dc3769196924	0.55
1 step below	unchecked	Dimensionality reduction revealed that the raw pLM-embeddings from unlabeled data captured some biophysical features of protein sequences.this claim takes its method from it, as the citing paper says · human literature · ext:9fca9c22b5d55e11	0.55
this claim	unchecked	Critically, EvoDiff can generate proteins inaccessible to structure-based models, such as those with disordered regions, while maintaining the ability to desig…human literature · ext:1a15ce17804bcaa3	0.55

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