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双引擎论文搜索

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使用 OpenAlex 与 AnySearch 两个真实数据源并行搜索、交叉匹配和输出可追溯论文元数据。

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Source SKILL.md: https://github.com/XiaoMaColtAI/math-modeling-skill/blob/HEAD/tools/paper_search/SKILL.md

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双引擎论文搜索

数据源

  • OpenAlex：结构化学术元数据。
  • AnySearch Academic：学术垂直搜索，支持当前 MCP Markdown 响应解析。

默认并行调用两个引擎。DOI 相同的记录直接交叉验证；无 DOI 时仅在标题高度相似且年份相容时合并。同一引擎中标题规范化后相同的预印本与正式出版记录也会折叠，并优先保留引用信息和元数据更完整的记录。交叉匹配结果、OpenAlex 独有结果和 AnySearch 独有结果分开输出。

融合时按查询词覆盖率过滤和重排，相关性优先于引用量，避免高被引但主题无关的论文挤占结果。包含多个专业术语时，候选文献至少命中两个有效查询词；这一阈值兼顾缺少摘要的元数据，不能代替人工核验。物理、材料和光学主题应组合使用材料名、机理名与模型名，例如 Sellmeier 4H-SiC Fabry-Perot；结果过少时逐步放宽查询，不直接接受无关结果。

使用

python scripts/hybrid_scholar.py --query "robust optimization vehicle routing" --limit 10 --json

如 AnySearch 需要鉴权：

$env:ANYSEARCH_API_KEY = "<密钥>"
python scripts/hybrid_scholar.py --query "analytic hierarchy process" --limit 8

诊断单个引擎时可用 --openalex-only 或 --anysearch-only；正式文献检索默认不得只运行一个引擎。

核验规则

  1. 搜索结果只用于发现候选文献。
  2. 引用前打开 DOI 或出版机构页面核对作者、题名、年份、期刊/会议、卷期页。
  3. 不把引用量当作正确性的证明。
  4. 不根据标题或摘要编造不存在的结论。
  5. 输出中保留 sources 和 cross_validated 状态。