Derivative of \( \displaystyle \frac{e^{x - 1}}{x} \)
Problem 2.340 · hard
Differentiate \( \displaystyle f(x) = \frac{e^{x - 1}}{x} \).
- \[ \frac{d}{d x} \frac{e^{x - 1}}{x} \]rewriteStart with the derivative of the function. Rewrite the quotient as a product.✓ Proved
- \[ = e^{x - 1} \frac{d}{d x} \frac{1}{x} + \frac{\frac{d}{d x} e^{x - 1}}{x} \]productApply the product rule.✓ Proved
- \[ = e^{x - 1} \frac{d}{d x} \frac{1}{x} + \frac{e^{x - 1}}{x} \]derivativeDifferentiate the first term.✓ Proved
- \[ = \frac{e^{x - 1}}{x} - \frac{e^{x - 1}}{x^{2}} \]derivative algebraDifferentiate the second term. Simplify the signs.✓ Proved
- \[ = \left(\frac{1}{x} - \frac{1}{x^{2}}\right) e^{x - 1} \]algebraFactor out the common term.✓ Proved
- \[ = \frac{\left(x - 1\right) e^{x - 1}}{x^{2}} \]simplifyCombine the terms into a single fraction.✓ Proved
Answer \( \frac{\left(x - 1\right) e^{x - 1}}{x^{2}} \)
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
| Line | Status | Checked by | Detail |
|---|---|---|---|
| 1 | ✓ Proved | sympy 1.14.0 | line 1 is the problem as stated |
| 2 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 undefined where x = 0 |
| 3 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 undefined where x = 0 |
| 4 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 undefined where x = 0 |
| 5 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 undefined where x = 0 |
| 6 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 undefined where x = 0 |
| 7 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 undefined where x = 0 |
| 8 | ✓ Proved | sympy 1.14.0 | simplify(a - b) reduced to 0 undefined where x = 0 |
| answer | ✓ Proved | sympy 1.14.0 | final line against the stated answer: simplify(a - b) reduced to 0 undefined where x = 0 |
| answer, a second way | ✓ Proved | sympy 1.14.0 | SymPy differentiated f directly and got the stated answer |
Reviewers
gpt-oss:20b: passdeepseek-r1:70b: fail (style) — Step 1 lacks a rule label, which should be specified for clarity.qwen3.6:27b-mlx: inconclusive — reviewer response could not be parsed: { "verdict": "fail", "severity": "error", "notes": "Step 4 is labeled 'derivative' but only differentiates the first term of the product while leaving the second term's derivative unevaluated. The 'de
Every verdict on record (13)
qwen3.6:27b-mlx: inconclusive 2026-09-20 — reviewer response could not be parsed: { "verdict": "fail", "severity": "error", "notes": "Step 4 is labeled 'derivative' but only differentiates the first term of the product while leaving the second term's derivative unevaluated. The 'degpt-oss:20b: pass 2026-09-20qwen3.6:27b-mlx: fail (error) 2026-09-20 — Step 4 is mathematically incorrect because it fails to apply the chain rule when differentiating exp(x - 1), omitting the derivative of the inner function (which is 1). Additionally, Step 5 applies the derivative rule to only one term of the sum, violating the 'one thing per step' constraint.gpt-oss:20b: pass 2026-09-20qwen3.6:27b-mlx: inconclusive 2026-09-19 — reviewer response could not be parsed: { "verdict": "fail", "severity": "error", "notes": "Step 4 is labeled 'derivative' but only differentiates the first term of the product while leaving the second term's derivative as an unsolved operadeepseek-r1:70b: fail (style) 2026-09-19 — Step 1 lacks a rule label, which should be specified for clarity.gpt-oss:20b: pass 2026-09-19qwen3.6:27b-mlx: fail (error) 2026-09-19 — Step 4 is labeled 'derivative' but only differentiates the first term of the product rule expansion, leaving the second term (exp(x - 1) * Derivative(1/x, x)) untouched. This violates the 'one thing per step' rule; it should be labeled 'sum' or split into two steps.deepseek-r1:70b: pass 2026-09-19gpt-oss:20b: pass 2026-09-19qwen3.6:27b-mlx: fail (error) 2026-09-18 — Step 4 is labeled 'derivative' but fails to apply the chain rule to differentiate exp(x - 1), incorrectly leaving the derivative as exp(x - 1) instead of exp(x - 1). This results in an incorrect intermediate expression.deepseek-r1:70b: pass 2026-09-18 — Step 1 lacks a rule label, which is a minor style issue.gpt-oss:20b: pass 2026-09-18
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 2026-09-26 with SymPy 1.14.0.