There is a rigorous definition of bias, and that isn’t it. That is called ‘variance’. It doesn’t matter if there is structure to the variance. It doesn’t matter

There is a rigorous definition of bias, and that isn’t it. That is called ‘variance’. It doesn’t matter if there is structure to the variance. It doesn’t matter if the model is consistently wrong for one type of input. It is not bias unless it has been specifically and intentionally programmed to predict something other than the result from the maximum likelihood estimator given the data. A trickier type of bias is in the dataset itself, but once again, this would require a specific effort and intention to produce that bias by modifying the collection or filtering procedure. Nothing as much has been alleged, so you have provided no evidence of bias, ‘systemic’ or otherwise. Come up with a different word. Maybe “non-uniform variance”.