One way to mitigate this problem is to use energy correcting methods to achieve higher accuracy via correcting energies from lower level methods. Building ML based delta correction models or simple statistics based correction schemes that are widely applicable, requires large datasets or reaction energies from both cheap/low-fidelity and expensive/high-fidelity methods.