仓库/Skill 库

AI4Scholar for DeepSeek Harness (dsh)：38 个原生学术工具——Semantic Scholar、PubMed、Google Scholar、arXiv、bioRxiv/medRxiv、DOI、full text、auto-cite、figures、unified search。由 ai4scholar.net 提供支持AI4Scholar for DeepSeek Harness (dsh): 38 native academic tools — Semantic Scholar, PubMed, Google Scholar, arXiv, bioRxiv/medRxiv, DOI, full text, auto-cite, figures, unified search. Powered by ai4scholar.net

AI4Scholar for DeepSeek Harness (dsh)：38 个原生学术工具——Semantic Scholar、PubMed、Google Scholar、arXiv、bioRxiv/medRxiv、DOI、全文、自动引用、图表、统一搜索。由 ai4scholar.net 提供支持AI4Scholar for DeepSeek Harness (dsh): 38 native academic tools — Semantic Scholar, PubMed, Google Scholar, arXiv, bioRxiv/medRxiv, DOI, full text, auto-cite, figures, unified search. Powered by ai4scholar.net

本人毕业学年所有天体物理课题汇总。毕业设计聚焦轨道转移优化，采用梯度下降法及 Markov Chain Monte Carlo 方法进行不确定性评估These are all the astrophysics projects in my final year. My final-year project focuses on orbital transfer optimisation using gradient descent and the Markov Chain Monte Carlo method for uncertainty evaluation.

围绕矩匹配情景生成与时序投资组合评估的可复现研究。Reproducible research on moment-matching scenario generation and temporal portfolio evaluation

论文一：NL2SQL 歧义检测——M1.5 分类法、确定性基线、人工金标评估与可复现研究制品Paper 1: NL2SQL Ambiguity Detection — M1.5 taxonomy, deterministic baseline, human-gold evaluation, reproducible research artifact

面向人脸域去风格化、结构条件化、评估与质量过滤的紧凑型可复现研究流水线。Compact reproducible research pipeline for face-domain destylization, structural conditioning, evaluation, and quality filtering.

推进并系统评估 BV-BRC Copilot，从研究问题和已发表方法生成、执行并复现生物信息学工作流。Advancing and systematically evaluating BV-BRC Copilot for generating, executing, and reproducing bioinformatics workflows from research questions and published methods.

仓库包含文章与 Excel 文件，收录系统综述《人工智能方法在实体瘤疗效评价标准中的应用》中的 CLAIM 与 FUTURE-AI 评估。Repository containing articles and Excel files with CLAIM and FUTURE-AI assessments for the systematic review Artificial intelligence approaches to the Response Evaluation Criteria in Solid Tumors: a systematic review.

Research Loom 是 profile 驱动的 research harness，用于维持从研究问题与证据到发现、写作与发表的全链路可追溯性Research Loom is a profile-driven research harness for maintaining traceability from research questions and evidence through findings, writing, and publication.

面向本地学术文档研究：用户对多篇PDF/Markdown论文提问，Agent自主决定检索范围、读取文本/页面/图表证据、判断证据是否充分并生成带引用回答；过程实时可看、结果可离线评测。

GitHub Page 演示：服务于 2026 年文献综述的 Miscanthus 产量地图。Demonstration of GitHub Page with Miscanthus Yield mapping for Literature Review 2026

面向 MetaTrader 5 的可配置开盘区间突破 EA，附带可复现的研究 harness；所有参数均为输入项，兼容 Windows 与 Linux/WineConfigurable opening-range breakout EA for MetaTrader 5, with a reproducible research harness. Every parameter is an input; runs on Windows and Linux/Wine.

可复用的 Python 与 notebook 工作流，用于多语言科研数据准备、统计分析及 AI 文本检测器评估。Reusable Python and notebook workflows for multilingual research-data preparation, statistical analysis, and AI-text detector evaluation.