In the integration phase of this study, we used a method based on the use of BES-SSR anchoring points which was expected to be highly precise and accurate if the contig assembly had been performed well [ 22].
The simulation suggested that GC/MS distribution estimates can be expected to be very precise, but less accurate.
Nevertheless, QCT would be expected to be more precise for quantification of bone loss.
However, being a field-based inventory, estimates of parameters related to AGB and AGB changes derived from NAFORMA data are not expected to be sufficiently precise to meet the accuracy requirements for a REDD+ MRV system.
Note that this automated procedure is expected to be very precise for cognate TCS where the co-occurrence of three domains (HisKA, HATPase_c, Response_reg) ensures the high quality of the data set.
Due to the methods used to construct these item banks, such measures are expected to be more precise and less burdensome to patients to complete [ 53].
A system learnt using data obtained from a particular region can be expected to be more precise in performing mass screening in that same region.
What follows from the scheme is that the gain of the prediction error can be amplified for predicted (more likely) input to a larger extent as the predicted input is expected to be more precise.
Although GBS gave the estimated value incidentally closer to the suggested estimate than CGBS did, CGBS estimates can be expected to be more precise in general as shown in our simulation study.
Correcting this led to a significant effect of incomplete blocks in 07NC, which was therefore included in the updated model (BLUPs from the previous analysis are expected to be less precise, because the random effects of incomplete blocks were confounded with the random effect of RILs).
