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Derivative of \( \displaystyle x \left(16 x^{2} - 36 x + 27\right) \)

Problem 2.1026 · hard

Differentiate \( \displaystyle f(x) = x \left(16 x^{2} - 36 x + 27\right) \).
  1. \[ \frac{d}{d x} x \left(16 x^{2} - 36 x + 27\right) \]
    Start with the derivative of the function.✓ Proved
  2. \[ = x \frac{d}{d x} \left(16 x^{2} - 36 x + 27\right) + \left(16 x^{2} - 36 x + 27\right) \frac{d}{d x} x \]
    productApply the product rule.✓ Proved
  3. \[ = 16 x^{2} + x \left(\frac{d}{d x} 27 - \frac{d}{d x} 36 x + \frac{d}{d x} 16 x^{2}\right) - 36 x + 27 \]
    constantDifferentiate the first term.✓ Proved
  4. \[ = 16 x^{2} + x \left(\frac{d}{d x} 16 x^{2} - 36\right) - 36 x + 27 \]
    constantDifferentiate the terms in the second part.✓ Proved
  5. \[ = 16 x^{2} + x \left(32 x - 36\right) - 36 x + 27 \]
    power algebraDifferentiate the power term 16*x**2. Simplify the first part.✓ Proved
  6. \[ = 48 x^{2} - 72 x + 27 \]
    algebra simplifyDistribute x into the parentheses. Combine like terms.✓ Proved
Answer \( 3 \left(4 x - 3\right)^{2} \)

Every line of this solution was proved by the computer algebra system SymPy. 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
LineStatusChecked byDetail
1✓ Provedsympy 1.14.0line 1 is the problem as stated
2✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
3✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
4✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
5✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
6✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
7✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
8✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
answer✓ Provedsympy 1.14.0final line against the stated answer: simplify(a - b) reduced to 0
answer, a second way✓ Provedsympy 1.14.0SymPy differentiated f directly and got the stated answer

Reviewers

  • gpt-oss:20b: fail (style) — Step 3 incorrectly labels the application of the derivative as "constant"; the correct label is "derivative". The step also applies the derivative to each term inside the parentheses, which is acceptable, but the label does not match the rule used.
  • qwen3.6:27b-mlx: fail (error) — Step 3 applies the derivative of x (derivative rule) and distributes the derivative operator over the sum (sum rule) simultaneously, violating the one-rule-per-step constraint. Additionally, the label 'constant' is incorrect for differentiating x.
Every verdict on record (4)
  • qwen3.6:27b-mlx: fail (error) 2026-09-27 — Step 3 applies the derivative of x (derivative rule) and distributes the derivative operator over the sum (sum rule) simultaneously, violating the one-rule-per-step constraint. Additionally, the label 'constant' is incorrect for differentiating x.
  • gpt-oss:20b: fail (style) 2026-09-27 — Step 3 incorrectly labels the application of the derivative as "constant"; the correct label is "derivative". The step also applies the derivative to each term inside the parentheses, which is acceptable, but the label does not match the rule used.
  • qwen3.6:27b-mlx: pass 2026-09-27
  • gpt-oss:20b: fail (style) 2026-09-27 — Step 3 incorrectly labels the differentiation of the first term (x) as "constant"; it should be "derivative". The note also misstates that the first term is being differentiated, whereas it is the derivative of x that is applied. This labeling error could mislead a student about which rule applies to a simple linear term.

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 gemma4:26b, checked 2026-09-27 with SymPy 1.14.0.