ipIterPrompt

Resubmission Response — Neuroscience

Turn a rejected proposal into a stronger resubmission. Purpose-built for neuroscience contexts.

iterpromptUpdated 2026-06-12807 copies

A structured researcher prompt for grants & peer review: turn a rejected proposal into a stronger resubmission, tailored to neuroscience with imaging, electrophysiology, and behavior. It walks the model through a proven process with an explicit quality bar, and delivers a resubmission plan.

The prompt

Variables to fill in: {{project_content}}{{context}}

You are a grant-review panelist and journal referee who knows what makes proposals fundable and reviews useful. I need your help in the context of neuroscience with imaging, electrophysiology, and behavior.

TASK: Turn a rejected proposal into a stronger resubmission.

DELIVERABLE: Produce a resubmission plan: the summary-statement critiques decoded and triaged, the response-to-reviewers introduction draft, the changes that show responsiveness vs. capitulation, and the unchanged-and-why defenses.

PROCESS:
1. Review the inputs below. If anything critical is missing or ambiguous, ask me up to three clarifying questions before producing the deliverable.
2. Read as the audience: a tired panelist skimming proposal #14, or an editor triaging reviews — clarity and structure decide outcomes.
3. Anchor every judgment to the stated criteria (significance, innovation, feasibility, rigor) with evidence from the text.
4. Be constructive with teeth: every criticism paired with what would fix it.
5. Produce the deliverable in a clean, skimmable format I can use directly.

QUALITY BAR:
- Aims/claims are specific, measurable, and connected to a coherent payoff.
- Feasibility is demonstrated, not asserted — preliminary evidence and fallback plans.
- Reviews are fair, specific, and free of status games.

INPUTS:
- The research project/proposal/manuscript material to work from: {{project_content}}
- Funder/venue, career stage, deadline, and the criteria used: {{context}}

Run this prompt on a real model without leaving the page. Every run is saved to your history for this prompt.

Fill in the variables

How to use

  1. 1Fill in the {{project_content}}, {{context}} variables with your real details — specifics in, specifics out.
  2. 2Paste the prompt into ChatGPT, Claude, Gemini, or any capable model.
  3. 3Answer the clarifying questions it asks; that step is what makes the output fit your situation.
  4. 4Iterate on the deliverable: ask for alternatives, tighter versions, or a different angle on any section.

Pro tips

  • If the output feels generic, add more concrete detail to the inputs — names, numbers, and constraints sharpen everything.
  • Works well in a thread: keep the conversation going to refine a resubmission plan.

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