prioritization

Prioritization

When to Use This Skill

• When you have multiple hypotheses and need to choose which to test first
• When you're deciding between exploring new areas vs deepening current investigation
• When iteration budget is running low and you need to focus

The Core Question

"What will provide the most scientific insight right now?"

Prioritization Framework

Option 1: Test a Hypothesis

Priority = Impact × Feasibility × Novelty

Rate each hypothesis:

• Impact (1-5): How central to research question?
• Feasibility (1-5): Can we test it with current data?
• Novelty (1-5): Is this a new insight?

Test highest-scoring hypothesis first.

Example:

H1: "Salvage flux is increased"
  Impact=4, Feasibility=4, Novelty=3 → Score=48

H2: "CMP→CDP bottleneck"
  Impact=5, Feasibility=5, Novelty=4 → Score=100 ⭐ Test this

H3: "Sex differences modulate effect"
  Impact=2, Feasibility=3, Novelty=2 → Score=12

Option 2: Explore Data

When to prioritize exploration:

• ✅ Early iterations (< 10% of budget)
• ✅ You're stuck and need fresh ideas
• ✅ Current hypotheses are all low-priority
• ✅ You haven't looked at key variable types yet

When NOT to explore:

• ❌ Late iterations (> 80% of budget)
• ❌ You have high-priority hypotheses ready to test
• ❌ You're avoiding testing a difficult hypothesis

Option 3: Search Literature

When to prioritize literature:

• ✅ Before testing a hypothesis (to inform design)
• ✅ After unexpected result (to understand mechanism)
• ✅ When hypothesis was rejected (to generate alternatives)
• ✅ Early iterations (build knowledge foundation)

When NOT to search:

• ❌ As procrastination (avoiding analysis)
• ❌ Late iterations when you should be synthesizing
• ❌ You already searched this topic

Option 4: Record/Synthesize Findings

When to prioritize synthesis:

• ✅ You've confirmed a finding but haven't recorded it
• ✅ Late iterations (> 70% of budget)
• ✅ You have 3+ findings that might be related
• ✅ You're approaching iteration limit