Running a Literature Review With AI

End-of-lesson check

15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-creators-literature-review-with-ai

1. What is the core idea behind "Running a Literature Review With AI"?

   1. AI turns weeks of literature review into days — if you know how to use it. Here is a workflow that actually works.
   2. What sampling temperature?
   3. Emergent behaviors: the whole is more than its labeled parts
   4. LessWrong, Alignment Forum — AI-curious audience

2. Which term best describes a foundational idea in "Running a Literature Review With AI"?

   1. Elicit
   2. literature review
   3. Semantic Scholar
   4. NotebookLM

3. A learner studying Running a Literature Review With AI would need to understand which concept?

   1. literature review
   2. Semantic Scholar
   3. Elicit
   4. NotebookLM

4. Which of these is directly relevant to Running a Literature Review With AI?

   1. literature review
   2. Elicit
   3. NotebookLM
   4. Semantic Scholar

5. Which of the following is a key point about Running a Literature Review With AI?

   1. Frame: write one sentence defining what you want to learn
   2. Harvest: use Semantic Scholar, Elicit, or Perplexity to surface 30-80 candidate papers
   3. Filter: skim abstracts manually — AI cannot judge relevance to your specific question yet
   4. Read and synthesize: batch-read with Claude or NotebookLM, then write your own summary

6. Which of these does NOT belong in a discussion of Running a Literature Review With AI?

   1. Frame: write one sentence defining what you want to learn
   2. What sampling temperature?
   3. Harvest: use Semantic Scholar, Elicit, or Perplexity to surface 30-80 candidate papers
   4. Filter: skim abstracts manually — AI cannot judge relevance to your specific question yet

7. Which statement is accurate regarding Running a Literature Review With AI?

   1. Top of file: one-sentence summary and main claim
   2. List of surprising findings
   3. One file per paper (slug-case-title.md)
   4. Limitations you noticed

8. Which of these does NOT belong in a discussion of Running a Literature Review With AI?

   1. One file per paper (slug-case-title.md)
   2. Top of file: one-sentence summary and main claim
   3. List of surprising findings
   4. What sampling temperature?

9. What is the key insight about "Triangulate, always" in the context of Running a Literature Review With AI?

   1. Never trust one tool's synthesis. Ask two tools the same question; where they disagree, read the papers yourself.
   2. What sampling temperature?
   3. Emergent behaviors: the whole is more than its labeled parts
   4. LessWrong, Alignment Forum — AI-curious audience

10. What is the key insight about "Hallucination is real" in the context of Running a Literature Review With AI?

    1. What sampling temperature?
    2. Every year, researchers cite papers that do not exist because an AI made them up.
    3. Emergent behaviors: the whole is more than its labeled parts
    4. LessWrong, Alignment Forum — AI-curious audience

11. What is the recommended tip about "Ground your practice in fundamentals" in the context of Running a Literature Review With AI?

    1. What sampling temperature?
    2. Emergent behaviors: the whole is more than its labeled parts
    3. Every AI capability has an underlying mechanism. Understanding that mechanism tells you where it'll fail — which is more…
    4. LessWrong, Alignment Forum — AI-curious audience

12. Which statement accurately describes an aspect of Running a Literature Review With AI?

    1. What sampling temperature?
    2. Emergent behaviors: the whole is more than its labeled parts
    3. LessWrong, Alignment Forum — AI-curious audience
    4. A traditional literature review on a narrow AI topic takes weeks of reading abstracts, taking notes, and chasing citations.

13. What does working with Running a Literature Review With AI typically involve?

    1. The big idea: AI accelerates literature review but does not replace the thinking. Use it as a pair, not a proxy.
    2. What sampling temperature?
    3. Emergent behaviors: the whole is more than its labeled parts
    4. LessWrong, Alignment Forum — AI-curious audience

14. Which best describes the scope of "Running a Literature Review With AI"?

    1. It is unrelated to foundations workflows
    2. It focuses on AI turns weeks of literature review into days — if you know how to use it. Here is a workflow that a
    3. It applies only to the opposite beginner tier
    4. It was deprecated in 2024 and no longer relevant

15. Which section heading best belongs in a lesson about Running a Literature Review With AI?

    1. What sampling temperature?
    2. Emergent behaviors: the whole is more than its labeled parts
    3. A four-stage workflow
    4. LessWrong, Alignment Forum — AI-curious audience