In my experience, $Z_{\alpha}$ indicates the critical value where the right-tailed area under a standard normal distribution is $\alpha$, i.e.
$$P(Z > Z_\alpha) = \alpha$$
With this rule, if $\alpha = 0.05$, then
$$Z_{\frac{\alpha}{2}} = Z_{0.025} = 1.96 ~~~\text{and}~~~~ Z_{1-\frac{\alpha}{2}} = Z_{0.975} = -1.96.$$
However, in some internet sources, $Z_{\alpha}$ is defined as the inverse function of the standard normal CDF, i.e.
$$P(Z < Z_\alpha) = \alpha$$
which makes the example above have opposite signs:
$$Z_{\frac{\alpha}{2}} = -1.96 ~~~\text{and}~~~~ Z_{1-\frac{\alpha}{2}} = 1.96.$$
They make me confused about how to use correct symbols in the confidence intervals or test statistics. Is there a precise mathematical definition of $Z_{\alpha}$?