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Derivative of \( \displaystyle \ln{\left(\frac{e^{3 x}}{3 x} \right)} \)

Problem 2.1138 · hard Beautiful

Differentiate \( \displaystyle f(x) = \ln{\left(\frac{e^{3 x}}{3 x} \right)} \).
  1. \[ \frac{d}{d x} \ln{\left(\frac{e^{3 x}}{3 x} \right)} \]
    Start with the derivative of the function.✓ Proved
  2. \[ = \frac{d}{d x} \left(3 x - \ln{\left(3 x \right)}\right) \]
    simplify simplifyUse logarithm properties to split the expression. Simplify the log of the exponential term.✓ Proved
  3. \[ = \frac{d}{d x} 3 x - \frac{d}{d x} \ln{\left(3 x \right)} \]
    sumApply the difference rule.✓ Proved
  4. \[ = 3 - \frac{d}{d x} \ln{\left(3 x \right)} \]
    constant-multipleDifferentiate the first term.✓ Proved
  5. \[ = 3 - \frac{\frac{d}{d x} 3 x}{3 x} \]
    chainApply the chain rule to the logarithm.✓ Proved
  6. \[ = 3 - \frac{1}{x} \]
    derivative algebraDifferentiate the linear term. Simplify the fraction.✓ Proved
  7. \[ = \frac{3 x - 1}{x} \]
    simplifyCombine into a single fraction.✓ Proved
Answer \( 3 - \frac{1}{x} \)
Mind the domain. The answer is also defined on (-oo, 0), where f(x) is not. Substituting there gives a number that is not a slope of f.

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
log is undefined for non-positive arguments
undefined where x = 0
3✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
4✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
5✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
6✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
undefined where x = 0
7✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
undefined where x = 0
8✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
undefined where x = 0
9✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
undefined where x = 0
answer✓ Provedsympy 1.14.0final line against the stated answer: simplify(a - b) reduced to 0
undefined where x = 0
answer, a second way✓ Provedsympy 1.14.0SymPy differentiated f directly and got the stated answer

Reviewers

  • gpt-oss:20b: fail (style) — Step 1 lacks a rule label; every step must name a rule from the allowed vocabulary.
  • qwen3.6:27b-mlx: fail (error) — Step 5 is labeled 'constant-multiple' but performs the differentiation of the first term (derivative of 3x is 3). The rule 'constant-multiple' factors out constants, it does not compute derivatives. This is a mislabeling of the operation performed.
Every verdict on record (4)
  • qwen3.6:27b-mlx: fail (error) 2026-09-28 — Step 5 is labeled 'constant-multiple' but performs the differentiation of the first term (derivative of 3x is 3). The rule 'constant-multiple' factors out constants, it does not compute derivatives. This is a mislabeling of the operation performed.
  • gpt-oss:20b: fail (style) 2026-09-28 — Step 1 lacks a rule label; every step must name a rule from the allowed vocabulary.
  • qwen3.6:27b-mlx: pass 2026-09-28 — The solution correctly applies logarithmic properties, the sum rule, and the chain rule. Each step isolates a single transformation, and the labels accurately reflect the operations performed.
  • gpt-oss:20b: fail (style) 2026-09-28 — Step 5 incorrectly labels the differentiation of 3*x as "constant-multiple"; it should be "derivative". The rest of the steps are fine.

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 2026-09-28 with SymPy 1.14.0.