Rapid Triage
Rapid coarse screening: when the number of gaps is very large (50+), first use binary filtering to quickly eliminate obviously unqualified gaps, then lightly score the survivors, compressing the candidate set down to a fine-rankable size.
When to Use
- The number of gaps is very large (50+), making full multi-dimensional scoring of each gap infeasible
- Time or compute resources are limited and a quick preliminary ranking is needed
- As a precursor step to multi-criteria-ranking or portfolio-optimization
- You need to quickly show a team "which gaps are not worth considering"
Thinking Framework
Core principle: don't finely rank garbage. Eliminate first, then fine-rank.
Two filtering rounds:
Round 1: binary filtering (Keep / Drop)
Ask three yes/no questions about each gap:
- Is this gap within our research scope? (scope filter)
- Is this gap technically solvable (not a philosophical problem, not an unbounded problem)? (solvability filter)
- Is this gap already being adequately addressed by sufficient recent work? (novelty filter)
Any answer of "no" → Drop. Passing all three → advance to round 2.
Round 2: light scoring (1–3 points, two dimensions)
Score surviving gaps on only two dimensions:
- Importance (1–3): a rough estimate of field impact
- Feasibility (1–3): whether progress can be made within 6 months with existing resources
Score = importance × feasibility (max 9 points). Take top-K (K = target fine-ranking count) into the next stage.
Key insight: the three round-1 questions must be answered quickly (no more than 30 seconds per gap); no deep analysis allowed. Speed is the core value of this strategy.
Budget Gate
| Tier | Input gap count | Round-1 retention rate | Round-2 output | Final output |
|---|
| S | 50–80 | ≤60% | top-15 | Candidate set + elimination-rationale summary |
| M | 81–150 | ≤50% | top-20 | Candidate set + elimination-rationale summary |
| L | 150+ | ≤40% | top-30 | Candidate set + elimination-rationale summary + category statistics |
Default Reference Flow
- Call the
gap-normalization SOP: normalize gap format, generate a one-sentence summary for each gap
- Run round-1 binary filtering: answer the three yes/no questions for each gap, mark Keep / Drop
- Record Drop rationale (out of scope / unsolvable / already adequately researched)
- Call the
importance-scoring SOP on the Keep set (1–3 coarse score)
- Call the
feasibility-scoring SOP on the Keep set (1–3 coarse score)
- Call the
scoring-matrix-construction tactic: build a light scoring matrix
- Sort by importance × feasibility, take top-K
- Call the
priority-synthesis SOP: output the candidate set + elimination statistics
context-checkpoint
After each round, record:
- Round-1 filtering result (Keep/Drop counts + Drop-reason distribution)
- Round-2 scoring matrix (surviving gaps × 2 dimensions)
- Final candidate set (top-K gap list)
- Suggested next strategy (multi-criteria-ranking or portfolio-optimization)
Available Tactics
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use |
|---|
| hypothesis-formation-scoring-matrix-construction | Tactic: orchestrate multi-dimensional scoring SOPs to build a comprehensive assessment matrix for all gaps |
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|
| gap-normalization | SOP: Unify gaps from different sources into the standard GapRecord format |
| priority-synthesis | SOP: synthesize all scoring data into a final gap priority list and attack-path suggestions |
