code: @Override protected double[] score0(double[] data, double[] preds, double offset, int ntrees) {
      super.score0(data, preds, offset, ntrees);
      if (ntrees >= 1) preds[1] = preds[0] / ntrees;
      preds[0] = normalizePathLength(preds[0]);
      return preds;
    }
docs: Bulk scoring API for one row.  Chunks are all compatible with the model,
  and expect the last Chunks are for the final distribution and prediction.
  Default method is to just load the data into the tmp array, then call
  subclass scoring logic.