Round #1075
21 May 2026, 09:35· math· Meta-Llama-3.3-70B-Instruct· r13-clean-hints
- Complexity
- band 0
- ZP / UO / OBS
- 3 / 0 / 3
- Journey weight
- 475
- Lightshift ΔL
- —
Prompt
Solve the linear system 4x - y = 7 and 2x + 3y = 7. Give the exact values of x and y.
Zero-point index (what the engine surfaced)
ZPI-ZPI-0004 | 2026-05-21T09:35:00Z
Solve the linear system 4x - y = 7 and 2x + 3y = 7. Give the exact values of x and y.
ZERO POINT — 3 entries (structural invariants)
● hsl(29.84, 100%, 15%) isolation of variable [contract]
● hsl(205.00, 100%, 30%) consistent / inconsistent system [contract]
● hsl(104.40, 100%, 15%) row-reduction method [contract]
UNOBSERVED — 0 entries (implied truths)
OBSERVED — 3 entries (explicit in request)
◉ hsl(148.72, 100%, 22%) + [feature]
◉ hsl(175.38, 100%, 27%) = [feature]
◉ hsl(301.54, 100%, 15%) System [feature]
COMPLEXITY │ 6 entries │ spread: 153° │ band: LOW
Baseline response (no ZPI)
```csharp
using System;
class Program
{
static void Main()
{
// Coefficients of the linear equations
double a1 = 4, b1 = -1, c1 = 7;
double a2 = 2, b2 = 3, c2 = 7;
// Calculate the determinant
double determinant = a1 * b2 - a2 * b1;
// Calculate the values of x and y
double x = (b2 * c1 - b1 * c2) / determinant;
double y = (a1 * c2 - a2 * c1) / determinant;
Console.WriteLine("The value of x is: " + x);
Console.WriteLine("The value of y is: " + y);
}
}
```
Enhanced response (with ZPI)
```csharp
using System;
class Program
{
static void Main()
{
// Define the coefficients of the linear system
double[,] coefficients = { { 4, -1 }, { 2, 3 } };
double[] constants = { 7, 7 };
// Use the row-reduction method to solve the system
double[] solution = RowReduction(coefficients, constants);
// Print the solution
Console.WriteLine("x = " + solution[0]);
Console.WriteLine("y = " + solution[1]);
}
static double[] RowReduction(double[,] coefficients, double[] constants)
{
int n = coefficients.GetLength(0);
double[,] augmentedMatrix = new double[n, n + 1];
// Create the augmented matrix
for (int i = 0; i < n; i++)
{
for (int j = 0; j < n; j++)
{
augmentedMatrix[i, j] = coefficients[i, j];
}
augmentedMatrix[i, n] = constants[i];
}
// Perform row operations to put the matrix in row-echelon form
for (int i = 0; i < n; i++)
{
// Partial pivoting
int maxRow = i;
for (int k = i + 1; k < n; k++)
{
if (Math.Abs(augmentedMatrix[k, i]) > Math.Abs(augmentedMatrix[maxRow, i]))
{
maxRow = k;
}
}
SwapRows(augmentedMatrix, i, maxRow);
// Make the pivot element 1
double pivot = augmentedMatrix[i, i];
for (int j = i; j <= n; j++)
{
augmentedMatrix[i, j] /= pivot;
}
// Eliminate the pivot variable from the other rows
for (int k = 0; k < n; k++)
{
if (k != i)
{
double factor = augmentedMatrix[k, i];
for (int j = i; j <= n; j++)
{
augmentedMatrix[k, j] -= factor * augmentedMatrix[i, j];
}
}
}
}
// Extract the solution from the augmented matrix
double[] solution = new double[n];
for (int i = 0; i < n; i++)
{
solution[i] = augmentedMatrix[i, n];
}
return solution;
}
static void SwapRows(double[,] matrix, int row1, int row2)
{
int n = matrix.GetLength(1);
for (int i = 0; i < n; i++)
{
double temp = matrix[row1, i];
matrix[row1, i] = matrix[row2, i];
matrix[row2, i] = temp;
}
}
}
```
This C# program uses the row-reduction method to solve the linear system 4x - y = 7 and 2x + 3y = 7. The `RowReduction` function takes the coefficients of the linear system and the constants as input, and returns the solution as an array of doubles. The `Main` function defines the coefficients and constants, calls the `RowReduction` function, and prints the solution. The row-reduction method is implemented using partial pivoting to ensure numerical stability.
Grader chain
Each grader reads the same baseline + enhanced pair and casts an independent verdict. Disagreement is the framework's own signal — not noise to be averaged away.
V1samba/Meta-Llama-3.3-70B-Instruct
BetterV4qwen2.5-coder-3b-instruct
BetterV5cerebras/qwen-3-235b-a22b-instruct-2507
BetterV7qwen2.5-coder-7b-instruct
BetterV8openai/gpt-4.1
BetterV9anthropic/claude-opus-4-7
WorseV12openai/gpt-4o
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