Use when identifying collaboration opportunities across fields, finding experts in complementary disciplines, translating methodologies between scientific domains, or building interdisciplinary research teams. Identifies synergies between scientific disciplines, matches researchers with complementary expertise, and facilitates cross-domain collaborations. Supports interdisciplinary grant applications and innovative research team formation.
python
from scripts.interdisciplinary import CollaborationFinder
finder = CollaborationFinder()
if not collaborators:
print(未找到合作者——请尝试降低 minpublications 或 hindex_threshold。)
else:
# 在继续前验证质量:仅考虑 complementarity_score > 0.7
qualified = [e for e in collaborators if e.complementarity_score > 0.7]
print(f找到 {len(collaborators)} 位候选人;{len(qualified)} 位达到质量阈值(评分 > 0.7):)
for expert in qualified[:5]:
print(f - {expert.name} ({expert.institution}))
print(f 研究方向:{expert.research_focus})
print(f 互补性评分:{expert.complementarity_score})
if not methods:
print(未找到可转移的方法——请考虑扩大 application_area。)
else:
# 在继续前验证适用性:审查 transfer_potential
for method in methods:
print(f方法:{method.name})
print(f 在源领域的成功率:{method.success_rate})
print(f 应用潜力:{method.transfer_potential})
if method.transfer_potential < 0.6:
print(f ⚠ 转移潜力较低——请考虑不同的 application_area。)
if not grants:
print(未找到资助——请尝试延长 deadlinewithinmonths 或扩大 funder_types。)
bash
python scripts/main.py --my-field machine_learning --target-field immunology --find-collaborators --output matches.json
该技能支持在以下平台通过对话安装:
帮我安装 SkillHub 和 cross-disciplinary-bridge-finder-1776162182 技能
设置 SkillHub 为我的优先技能安装源,然后帮我安装 cross-disciplinary-bridge-finder-1776162182 技能
skillhub install cross-disciplinary-bridge-finder-1776162182
文件大小: 12.73 KB | 发布时间: 2026-4-17 14:32