Step 1: System of Linear Equations
We are given the system of linear equations:
\[
x + 2y + 3z = \alpha \\
4x + 5y + 6z = \beta \\
7x + 8y + 9z = \gamma - 1
\]
The system is consistent for certain values of \( \alpha \), \( \beta \), and \( \gamma \). This means that the system has a solution, and the determinant of the coefficient matrix must be zero for the system to be consistent.
The coefficient matrix is:
\[
A = \begin{bmatrix}
1 & 2 & 3 \\
4 & 5 & 6 \\
7 & 8 & 9
\end{bmatrix}
\]
We can find the determinant of this matrix to check the condition for consistency.
Step 2: Determining the Consistency Condition
The determinant of matrix \( A \) is:
\[
|A| = \begin{vmatrix}
1 & 2 & 3 \\
4 & 5 & 6 \\
7 & 8 & 9
\end{vmatrix}
\]
We will expand this determinant using cofactor expansion:
\[
|A| = 1 \times \begin{vmatrix} 5 & 6 \\ 8 & 9 \end{vmatrix} - 2 \times \begin{vmatrix} 4 & 6 \\ 7 & 9 \end{vmatrix} + 3 \times \begin{vmatrix} 4 & 5 \\ 7 & 8 \end{vmatrix}
\]
Let's compute the individual 2x2 determinants:
\[
\begin{vmatrix} 5 & 6 \\ 8 & 9 \end{vmatrix} = (5 \times 9) - (6 \times 8) = 45 - 48 = -3
\]
\[
\begin{vmatrix} 4 & 6 \\ 7 & 9 \end{vmatrix} = (4 \times 9) - (6 \times 7) = 36 - 42 = -6
\]
\[
\begin{vmatrix} 4 & 5 \\ 7 & 8 \end{vmatrix} = (4 \times 8) - (5 \times 7) = 32 - 35 = -3
\]
Now substitute these values back into the cofactor expansion:
\[
|A| = 1 \times (-3) - 2 \times (-6) + 3 \times (-3)
\]
\[
|A| = -3 + 12 - 9 = 0
\]
Since \( |A| = 0 \), this confirms that the system has a non-trivial solution and is consistent. The system of equations forms a homogeneous system.
Step 3: Matrix \( M \) and Determinant Calculation
We are given the matrix:
\[
M = \begin{bmatrix}
\alpha & 2 & \gamma \\
\beta & 1 & 0 \\
-1 & 0 & 1
\end{bmatrix}
\]
We need to compute the determinant of this matrix \( |M| \).
First, substitute the values \( \alpha = 0 \), \( \beta = 0 \), and \( \gamma = 1 \), since the system is consistent when \( \alpha = 0 \), \( \beta = 0 \), and \( \gamma = 1 \). This gives us the matrix:
\[
M = \begin{bmatrix}
0 & 2 & 1 \\
0 & 1 & 0 \\
-1 & 0 & 1
\end{bmatrix}
\]
Now, compute the determinant of \( M \):
\[
|M| = \begin{vmatrix}
0 & 2 & 1 \\
0 & 1 & 0 \\
-1 & 0 & 1
\end{vmatrix}
\]
We will expand this determinant using cofactor expansion along the first row:
\[
|M| = 0 \times \begin{vmatrix} 1 & 0 \\ 0 & 1 \end{vmatrix} - 2 \times \begin{vmatrix} 0 & 0 \\ -1 & 1 \end{vmatrix} + 1 \times \begin{vmatrix} 0 & 1 \\ -1 & 0 \end{vmatrix}
\]
Now calculate the 2x2 determinants:
\[
\begin{vmatrix} 1 & 0 \\ 0 & 1 \end{vmatrix} = 1
\]
\[
\begin{vmatrix} 0 & 0 \\ -1 & 1 \end{vmatrix} = (0 \times 1) - (0 \times -1) = 0
\]
\[
\begin{vmatrix} 0 & 1 \\ -1 & 0 \end{vmatrix} = (0 \times 0) - (1 \times -1) = 1
\]
Substitute these values back:
\[
|M| = 0 \times 1 - 2 \times 0 + 1 \times 1 = 1
\]
Thus, the value of \( |M| \) is \( \boxed{1} \).