Feasibility Scoring

Feasibility Scoring

Assess the attackability of a research gap, identify bottlenecks, and output a feasibility score.

HARD-GATE

Pipeline

1. Pre-check: verify the completeness of the input GapRecord
2. Method-availability assessment: is the existing methodological toolbox sufficient to attack this gap (1-5); reference: are there mature algorithms/frameworks to reuse
3. Data-accessibility assessment: are the required datasets/corpora publicly available (1-5); reference: existence of public datasets, data-scale requirements
4. Resource-requirement assessment: are compute/experiment resource needs within a reasonable range (1-5); reference: GPU needs, lab equipment, funding
5. Time-horizon assessment: can it be completed within a typical PhD/project cycle (1-5); reference: expected workload, dependency-chain length
6. Composite scoring: equal-weighted average of the four dimensions, kept to one decimal place; extract the main bottlenecks (dimensions with score ≤ 2)
7. Output: return the FeasibilityScore object

Output Format

{
  "gap_id": "gap_001",
  "dimension_scores": {
    "method_availability": { "score": 4, "rationale": "..." },
    "data_accessibility": { "score": 2, "rationale": "..." },
    "resource_requirements": { "score": 3, "rationale": "..." },
    "time_horizon": { "score": 3, "rationale": "..." }
  },
  "composite_score": 3.0,
  "bottlenecks": ["data_accessibility"],
  "overall_rationale": "Composite rationale (2-4 sentences)"
}