What does $o_n(1)$ mean?

I'm trying to read the following article, and in the abstract they write:
Let $\xi$ be a non-constant real-valued random variable with finite support, and let $M_n(\xi)$ denote a $n\times n$ random matrix with entries that are independent copies of $\xi$. For $\xi$ which is not uniform on its support, we show that:
$Pr[M_n(\xi) \text{ is singular}] = Pr[\text{zero row or column}]+ (1+o_n(1))Pr[\text{two equal (up to sign) rows or columns}]$.

What does $o_n(1)$ mean here?

As I understand it, this $o_n(1)$ is meant as the standard “little o” notation (when $v_n$ takes non-zero values, $u_n = o(v_n)$ means $\frac{u_n}{v_n} → 0$), except that because several variables are involved ($n$, $ξ$, $p$), they added the $n$ subscript to clarify that the limit is as $n$ goes to infinity, for fixed values of the other variables. A perhaps more standard notation for what they write as $$x = o_n(y)$$ would be $$x \underset{n→+∞}{=} o(y)$$

StackExchange Computer Science Q#167165, answer score: 3