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Its line of work

Using this approach to significantly improve the accuracy of ML-predicted formation energies and elastic moduli of hypothetical crystals, two novel ultra-incompressible hard materials MoWC2 (P63/mmc) and ReWB (Pca21) were identified and successfully synthesized via in-situ reactive spark plasma sintering from a screening of 399,960 transition metal borides and carbides.

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).
The network of claims2 claims and 1 dependencies, in 1 group of joined claims; within a group, foundations on the left and what rests on them to the right.2 claims, 1 step deep, Materials ScienceUsing this approach to significantly improve the accuracy of ML-predicted formation energies and elastic moduli of hypo… takes its method from Similarly, we show that MEGNet models trained on $\sim 60,000$ crystals in the Materials Project substantially outperfo… (identified in the literature)Similarly, we show that MEGNet models trained on $\sim 60,000$ crystals in the Materials Project substantially outperfo…: unchecked, credence 0.55, stakes 1.0, reliance 1.0Similarly, we show…Using this approach to significantly improve the accuracy of ML-predicted formation energies and elastic moduli of hypo…: unchecked, credence 0.55, stakes 4.2Using this approach…

● 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 4.2 the claim it is drawn around

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Every claim drawn, as a table
ClaimStatusCheckableCredenceUseStakesRests on
Similarly, we show that MEGNet models trained on $\sim 60,000$ crystals in the Materials Project substantially outperfo…○ uncheckedyes0.5501.0—
Using this approach to significantly improve the accuracy of ML-predicted formation energies and elastic moduli of hypo…○ uncheckedyes0.5504.2Similarly, we show that MEGNet models trained on $\sim 60,000$ crystals in the Materials Project substantially outperfo…

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Step by step

WhereStatusClaimCredence
1 step belowuncheckedSimilarly, we show that MEGNet models trained on $\sim 60,000$ crystals in the Materials Project substantially outperform prior ML models in the prediction of…this claim takes its method from it, as the citing paper says · human literature · ext:55e6a833de66db810.55
this claimuncheckedUsing this approach to significantly improve the accuracy of ML-predicted formation energies and elastic moduli of hypothetical crystals, two novel ultra-incom…human literature · ext:f118b14029032bf30.55

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