Bland and Altman[15] expanded this idea by graphically showing the difference in each point, the average difference and the limits of vertical match with the average of the two horizontal ratings. The resulting Bland-Altman plot shows not only the general degree of compliance, but also whether the agreement is related to the underlying value of the article. For example, two advisors could closely match the estimate of the size of small objects, but could disagree on larger objects. The first point will naturally lead to a link between the VCA and Bland-Altman agreements, which in turn are directly related to the term RC: while the Bland-Altman limit values exceed the average of all the differences between the peer-to-peer measures of 1.96 times the standard deviation of these differences (SD), the RC is equal to 2.77 times the standard deviation (Sw); Half the width of the Bland-Altman boundary values coincides with the RC in simple settings, since the standard deviation within the subject is then synonymous with standard measurement error (SEM): in some studies that focus only on the difference between minor measurements, as in our study 1, the data are ideally represented by Bland-Altman plots, possibly optimized by the transformation of the logs of the original data and by taking into account heterogeneity and/or trends on the mess scale [10,20]. In Study 1, we observed the duality between the Bland-Altman boundaries of concordance on one side and the corresponding RC on the other. In fact, several authors of recent contract studies have defined the repeatability coefficient (or reproducibility coefficient) at 1.96 times the standard deviation of type differences [21-25], algebraic equal to 2.77 times the standard deviation within the subject in simple settings, such as our study 1. Lodge et al. designated the RC as 2.77 times the standard deviation within the subject [26]. In biological research, where nothing can be considered absolute and accurate, as in physics, the accuracy of a new measurement method is considered assured when the measurement principle is sound and a number of measures do not deviate from a pre-defined standard or a series of measurements carried out using a recognized reference method. The acceptable deviation limit must be set arbitrarily from the outset. Accuracy is generally calculated and discussed with respect to standard deviations and coefficients of variation (CV), compliance percentages, standard measurement errors, and Bland-Altman parcels with appropriate compliance limits [6]. In their systematic review of the study of agreements published between 2007 and 2009, Zaki and colleagues concluded that the Bland-Altman approach is by far the most used (178 studies (85%), followed by the Pearson correlation coefficient (27%), and the comparison of averages (18%) [7] Although Bland-Altman plots have been proposed to compare two measurement methods [8-10], they have also been valuable when comparing two observers (inter-observer variability assessment) or repeated measurements of the same observer (assessment of intra-observer variability). However, the Bland-Altman approach was not designed to assess the variability of the inter-observer, with more than two observers, nor to study the different sources of variation in the data.