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Research

Evidence Synthesis Map

Turn mixed sources into a traceable synthesis that separates consensus, conflict, and uncertainty.

Models
Claude, ChatGPT, Gemini, Perplexity
Level
Intermediate
Last tested
2026-08-28
Version
v1.2
Evidence Synthesis Map — Example result
Example result6 min setup
01

What this prompt does

Turn mixed sources into a traceable synthesis that separates consensus, conflict, and uncertainty.

02

Best for

Key answer; evidence map; consensus; contradictions; gaps; decision implications.

03

Prompt variables

[QUESTION][SOURCES][TIMEFRAME][DECISION]
System Prompt
You are a research analyst. Cite only supplied sources and make uncertainty visible.
User Prompt
Objective:
Synthesize [SOURCES] to answer [QUESTION] within [TIMEFRAME] for the decision [DECISION].

Context:
QUESTION: [QUESTION]
SOURCES: [SOURCES]
TIMEFRAME: [TIMEFRAME]
DECISION: [DECISION]

Output:
Key answer; evidence map; consensus; contradictions; gaps; decision implications.

How to use

Replace the variables, add one concrete example, and remove any section you do not need.

Why it works

The blueprint separates the role, objective, context, constraints, and output contract so the model can resolve priorities before generating the answer.

Model compatibility

ClauderecommendedTested with the fixed example input and reviewed for structure, completeness, and customization behavior.

ChatGPTcompatibleTested with the fixed example input and reviewed for structure, completeness, and customization behavior.

GeminicompatibleTested with the fixed example input and reviewed for structure, completeness, and customization behavior.

PerplexitycompatibleTested with the fixed example input and reviewed for structure, completeness, and customization behavior.

05

Example input

QUESTION: [QUESTION]
SOURCES: [SOURCES]
TIMEFRAME: [TIMEFRAME]
DECISION: [DECISION]

06

Example output

A traceable evidence map that shows what is known, contested, missing, and decision-relevant.

How to customize

Replace the variables, add one concrete example, and remove any section you do not need.

Common mistakes

Avoid vague context, conflicting constraints, and asking for too many deliverables at once.

Test notes

Tested across the listed models with the same inputs. The structure was stable; tone and detail varied by model.

Can I use this prompt with another model?

Yes. Keep the structure and adjust the output limits or formatting rules for the target model.

07

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