Public articles linked to the same research event.
bioRxiv The work introduces semantic vaccinology and implements it as SemVac: publications linked to each protein are retrieved through PaperBLAST, condensed into a structured semantic profile, and an LLM is prompted to return an antigenicity probability; on a curated 246-protein bacterial benchmark the best of 14 general-purpose LLMs matched or exceeded the precision of the specialized predictor PLGDL, with open-weight Kimi K2 0905 offering the strongest performance-cost balance, predictions were robust to masking of vaccine keywords, reproducible across repeated inference, and generalized to a 1,200-protein cross-pathogen dataset; explicit chain-of-thought reasoning increased recall but lowered precision in every model tested; applied to the mpox virus proteome, SemVac recovered the established
The work introduces semantic vaccinology and implements it as SemVac: publications linked to each protein are retrieved through PaperBLAST, condensed into a structured semantic profile, and an LLM is prompted to return an antigenicity probability; on a curated 246-protein bacterial benchmark the best of 14 general-purpose LLMs matched or exceeded the precision of the specialized predictor PLGDL, with open-weight Kimi K2 0905 offering the strongest performance-cost balance, predictions were robust to masking of vaccine keywords, reproducible across repeated inference, and generalized to a 1,200-protein cross-pathogen dataset; explicit chain-of-thought reasoning increased recall but lowered precision in every model tested; applied to the mpox virus proteome, SemVac recovered the established
The work introduces semantic vaccinology and implements it as SemVac: publications linked to each protein are retrieved through PaperBLAST, condensed into a structured semantic profile, and an LLM is prompted to return an antigenicity probability; on a curated 246-protein bacterial benchmark the best of 14 general-purpose LLMs matched or exceeded the precision of the specialized predictor PLGDL, with open-weight Kimi K2 0905 offering the strongest performance-cost balance, predictions were robust to masking of vaccine keywords, reproducible across repeated inference, and generalized to a 1,200-protein cross-pathogen dataset; explicit chain-of-thought reasoning increased recall but lowered precision in every model tested; applied to the mpox virus proteome, SemVac recovered the established
The work introduces semantic vaccinology and implements it as SemVac: publications linked to each protein are retrieved through PaperBLAST, condensed into a structured semantic profile, and an LLM is prompted to return an antigenicity probability; on a curated 246-protein bacterial benchmark the best of 14 general-purpose LLMs matched or exceeded the precision of the specialized predictor PLGDL, with open-weight Kimi K2 0905 offering the strongest performance-cost balance, predictions were robust to masking of vaccine keywords, reproducible across repeated inference, and generalized to a 1,200-protein cross-pathogen dataset; explicit chain-of-thought reasoning increased recall but lowered precision in every model tested; applied to the mpox virus proteome, SemVac recovered the established