Deep learning interatomic potential for metal-doped silicon carbide nanotubes: Development, validation, and mechanical response

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score-all-pairs loads the render index and computes SSIM for every valid source/target combination. 235,625 comparisons, two modes: same-font (both characters in the same font) and cross-font (source in a supplemental font, target in a standard font).

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With respect to Rust, working with agents and seeing how the agents make decisions/diffs has actually helped me break out of the intermediate Rust slog and taught me a lot about the ecosystem by taking on more ambitious projects that required me to research and identify effective tools for modern Rust development. Even though I have technically released Rust packages with many stars on GitHub, I have no intention of putting Rust as a professional skill on my LinkedIn or my résumé. As an aside, how exactly do résumés work in an agentic coding world? Would “wrote many open-source libraries through the use of agentic LLMs which increased the throughput of popular data science/machine learning algorithms by an order of magnitude” be disqualifying to a prospective employer as they may think I’m cheating and faking my expertise?

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