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The multivariable chain rule

Problem 10.546 · easy

Let \( \displaystyle z = x y^{2} + 3 x \) with \( \displaystyle x = s t \), \( \displaystyle y = s + t \). Find \( \displaystyle \frac{\partial z}{\partial s} \) at \( \displaystyle s = 2 \), \( \displaystyle t = 0 \).

\[ \left[\begin{matrix}\frac{\partial}{\partial x} \left(x y^{2} + 3 x\right)\\\frac{\partial}{\partial y} \left(x y^{2} + 3 x\right)\end{matrix}\right] = \left[\begin{matrix}y^{2} + 3\\2 x y\end{matrix}\right] \]
∂z/∂x and ∂z/∂y.✓ Proved
∂z/∂s = (∂z/∂x)(∂x/∂s) + (∂z/∂y)(∂y/∂s).
\[ 0 \]
Substitute.✓ Proved

Answer \( 0 \)

Lines: 2 proved, 1 not checked. The answer was also checked a second way, without looking at the solution. The reviewers disagree about how one step is explained; every verdict is in the receipt.

The full receipt

Line	Status	Checked by	Detail
1	✓ Proved	sympy 1.14.0	simplify(lhs - rhs) reduced to 0
2	Not checked	—	a sentence; read, not computed
3	✓ Proved	sympy 1.14.0	simplify(lhs - rhs) reduced to 0
answer, a second way	✓ Checked independently	sympy 1.14.0 + mpmath 1.3.0	substituted first, then differenced numerically

Reviewers

gpt-oss:20b: pass
qwen3.6:27b-mlx: fail (error) — The solution fails to compute the partial derivatives of x and y with respect to s, nor does it evaluate the terms at the specified point (s=2, t=0). Instead, it provides a tautology '0=0' as the substitution step, which is mathematically unjustified and incorrect.

Every verdict on record (4)

gpt-oss:20b: pass 2026-10-12
qwen3.6:27b-mlx: fail (error) 2026-10-12 — The solution fails to compute the partial derivatives of x and y with respect to s, nor does it evaluate the terms at the specified point (s=2, t=0). Instead, it provides a tautology '0=0' as the substitution step, which is mathematically unjustified and incorrect.
gpt-oss:20b: pass 2026-10-12
qwen3.6:27b-mlx: fail (error) 2026-10-12 — The solution fails to compute the partial derivatives of x and y with respect to s, nor does it evaluate the chain rule expression at the given point (s=2, t=0). It merely states the formula and asserts '0=0' without showing the calculation that leads to the result.

Proved: SymPy reduced the difference between the two sides to zero. Checked independently: a separate method, named above, confirmed it. Checked numerically: the two sides agree at every sampled point, which is evidence, not proof. Reviewed: a model or a person read it; that is all a sentence can have. Solution by generator:structured/multivariable_chain_rule, checked 2026-10-12 with SymPy 1.14.0.