a)Growth rate, b) peak percentage prevalence, c) cumulative percentage prevalence, d) percentage of households with at least one case during the simulation period as a function of... by Joe Hilton (7003265)

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Peak and b) cumulative prevalence among the clinically vulnerable population as a percentage of the baseline values when (OOHI) is not implemented, and c) peak and d) cumulative pr... by Joe Hilton (7003265)

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a)Growth rate, b) peak percentage prevalence, c) cumulative percentage prevalence, d) percentage of households with at least one case during the simulation period as a function of... by Joe Hilton (7003265)

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Expected secondary attack ratios by size. by Joe Hilton (7003265)

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Fig 5 - by Joe Hilton (7003265)

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Parameter notation, choices, and sources for the age- and household structured infection model. by Joe Hilton (7003265)

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Estimated age cohort populations and numbers shielding from ONS data [52, 54], estimated age distribution of shielding population, and proportion of each age group shielding. by Joe Hilton (7003265)

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Convergence of model from initial conditions to exponential growth regime. by Joe Hilton (7003265)

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Fig 6 - by Joe Hilton (7003265)

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Estimated susceptible-infectious transmission probability by household size from House <i>et al.</i> [30]. by Joe Hilton (7003265)

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Performance metrics for ProSmith and previously published methods for DTA prediction on the random split of the Davis dataset. by Alexander Kroll (9304225)

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ProSmith outperforms the ESP model in the prediction of enzyme-substrate pairs especially for molecules with limited representation in the test data. by Alexander Kroll (9304225)

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Performance metrics for all three trained gradient boosting models with different input vectors and for their combined weighted mean prediction. by Alexander Kroll (9304225)

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The optimal ProSmith models combine predictions based on the multimodal Transformer Network with predictions based on separate numerical representations of proteins and small molec... by Alexander Kroll (9304225)

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Performance metrics for ProSmith and previously published methods for DTA prediction for different splitting scenarios. by Alexander Kroll (9304225)

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For accurate DTA predictions, ProSmith requires training on identical drugs but not on similar proteins. by Alexander Kroll (9304225)

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Replacing the final prediction layer of end-to-end trained Transformer Networks with gradient boosting models improves performance. by Alexander Kroll (9304225)

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Coefficient of determination <i>R</i>² of ProSmith for different splitting scenarios of the Davis dataset. by Alexander Kroll (9304225)

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We divided the ESP test set into subsets according to the number of positive data points with the same small molecule in the training set. by Alexander Kroll (9304225)

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Performance metrics for ProSmith and ESP for the prediction of enzyme-substrate pairs. by Alexander Kroll (9304225)

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