Interpreting the Chi-square value for steady-state affinity plots

In all the literature I've read, the Chi2 value is only discussed for fitting kinetic data. However on Biacore systems the steady-state affinity fits also contain a Chi2 value in the output. Could anyone help me interpret this parameter?

I understand that it represents the "goodness of fit" of the model but how to determine the cutoff for significance?

The Chi2-value is an indicator of the goodness of fit but is less affected by the large number of data points than the sum-of-squares or the R2. However, the Chi2 is difficult to interpret (1). First, it strongly depends on the average signal level and therefore a generally acceptable Chi2 cut-off cannot be established. Second, it is not well adapted for time series data, because there is typically a strong correlation between data points in close temporal proximity. However, the Chi2 can be used as a global measure of the residual noise. For a well-defined fit, the square root of Chi2 should be of the same magnitude as the noise level on the Y-axis. Always use the Chi2 in combination with other validations (e.g. visual inspection of residuals).
The standard deviation of the noise level of the instrument can be determined by analysing the baseline scatter while running buffer at a constant flow rate.

ref 1. Onell, A. and Andersson, K.; Kinetic determinations of molecular interactions using Biacore - minimum data requirements for efficient experimemtal design. J.Mol.Recognit. (18) 307-317; 2005.

kind regards
Arnoud