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As expected, the power increases as sample size grows.
The communication overhead remains unchanged as group size grows.
But this is not a scalable solution as table size grows with network size.
This results in expected efficiencies which approach optimal as problem size grows relative to number of processors.
Firstly, as the size grows the complexity of the organic synthesis increases and secondly, sensitivity to light-induced damage becomes a major issue if covalent bonds are broken.
However, designing efficient reliable transport protocols for multicast is a largely open issue, due to the problem of feedback implosion towards the sender as group size grows.
As team size grows, project numbers shrink, resulting in fewer preclinical candidates to emerge from the discovery pipeline.
Model performance (AUC) increases as datasets with fewer examples are excluded Fig. 3 Cross-validation experiment: best performing models as dataset size grows.
PS-IRV is more consistently the best performer as more of the smaller datasets are excluded Fig. 4 Simulated target-prediction experiment: AUC scores as dataset size grows.
This reveals a decreasing chance of finding communities as their size grows, with a clear cut-off above a certain threshold.
About 33%% of these datasets contain more than 100 molecules Fig. 2 Cross-validation experiment: AUC scores as dataset size grows.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com