学术写作
15 个 · organized/repo_cards · 六阶段二十任务 · 方向综述 →
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公开榜单只展示已收录项目;待复核与已排除项目仍保留在仓库总库,不在此页传播。
研究阶段概览 Research Workflow
| # | 方向 | 数量 | 代表仓库 Top 3 |
|---|---|---|---|
| 01 | 证据综述 | 409 | HiLab-git/SSL4MIS · hymie122/RAG-Survey · ChaokunHong/MetaScreener |
首次收录 近 14 天 · 按日期统计
2026-10-10
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organized/repo_cards · 学术方向;旧书签仍可访问,新统计不再使用这些字段。
方向榜单 Legacy
| 文献总结 | 409 | htlin222/meta-pipe · choxos/jev-reviewer · aurumz-rgb/ReviewAid |
01
htlin222/meta-pipe
由 Claude Code 驱动的端到端元分析自动化:AI 辅助文献综述、筛选、提取、分析与稿件生成,面向系统综述和临床证据合成。Claude Code-powered end-to-end meta-analysis automation: AI-assisted literature review, screening, extraction, analysis, and manuscript generation for systematic reviews and clinical evidence synthesis
+10/周
130 ★
02
choxos/jev-reviewer
系统综述的数据提取,直接引用自论文。向试验报告及其补充材料提交你的提取表单或 RoB 2、ROBINS-I、QUADAS-2、TIDieR 模板;Jev 指向具体行,每条答案均为带页码的逐字引用,由你核对后导出表格。文件保留在浏览器本地。Data extraction for systematic reviews, quoted from the papers. Ask a trial report and its supplements your extraction form or a RoB 2, ROBINS-I, QUADAS-2 or TIDieR template; Jev points at the lines, every answer is a verbatim quote with its page, you check it and export the table. Files stay in your browser.
+35/周
19 ★
03
aurumz-rgb/ReviewAid
面向 systematic review 和 evidence synthesis 的 AI 驱动全文筛选与数据提取。AI-Driven Full-Text Screening and Data Extraction for Systematic Reviews and Evidence Synthesis
12 ★
04
eliaswestonfarber/scienceai
一个用于科学文献分析的开源 agentic harness。可协调前沿模型提取数据、复现发现并执行系统综述,具备完整的溯源追踪能力。An open-source agentic harness for scientific literature analysis. Coordinates frontier models to extract data, replicate findings, and perform systematic reviews with full provenance tracking.
9 ★
05
686f6c61/Hermes-Research-PRISMA
一个可复现的 Hermes Agent 研究运行时,用于系统性文献综述、全文证据抽取、方法路由以及可审计的发表产出。A reproducible Hermes Agent research runtime for systematic literature reviews, full-text evidence extraction, methodological routing, and auditable publication artifacts.
5 ★
06
herbertkokholm/attest
针对 LLM 集成证据筛选(系统综述标题/摘要筛选)的筛选-自验证内核。Screening-and-self-validation kernel for LLM-ensemble evidence screening (systematic review title/abstract screening).
1 ★
07
sm0704/abstractScreening
系统综述工具:面向学生自我关怀与学业功能的全文筛选与 Covidence 数据提取。Systematic-review tooling: full-text screening and Covidence data extraction for self-compassion and academic functioning in students
0 ★
08
InvestmentMDideas/GLASS-Data-Extraction-Benchmark
面向系统综述数据抽取、证据定位与偏倚风险评估的冻结式(frozen)防泄漏基准。Frozen, leakage-aware benchmark for systematic-review data extraction, evidence localization, and risk-of-bias support
0 ★
09
huige66631/paper-reading-desk
证据优先的科研桌面工具,支持论文发现、PDF 证据抽取、论点分析、对比与文献综述综合Evidence-first research desk for paper discovery, PDF evidence extraction, claim analysis, comparison, and literature review synthesis.
0 ★
10
heyiamnotacoder/srmassistant
系统综述与 meta-analyses 的 AI 辅助筛选与数据提取。model-agnostic prompts、带 PRISMA reason codes 的双轮筛选、逐字段置信度评分,输出兼容 Rayyan/RevMan。AI-assisted screening and data extraction for systematic reviews & meta-analyses. Model-agnostic prompts, dual-pass screening with PRISMA reason codes, per-field confidence scores, Rayyan/RevMan-ready outputs.
0 ★
11
griffin300/private-research-mcp
隐私优先的本地 Web 研究 MCP server,集成 SearXNG、隔离 Tor 路径、证据抽取、排序与精确引用。Privacy-first local web research MCP server with SearXNG, isolated Tor paths, evidence extraction, ranking, and exact citations.
0 ★
12
gowtham-majjiga/ai-research-assistant
面向多源检索、证据抽取与带引用研究摘要的自主 AI 研究助手。Autonomous AI research assistant for multi-source retrieval, evidence extraction, and cited research summaries.
0 ★
13
edpenington/meltiro
基于 Agentic LLM 的系统综述数据提取。Agentic LLM-assisted data extraction for systematic reviews
0 ★
14
andreaslofberg/screened
系统综述的标题/摘要筛选(Cursor skill + 静态工作表)。Title/abstract screening for systematic reviews (Cursor skill + static worksheet)
0 ★
15
Ahmad-Fathinejad/Title-Abstract-Screening
SLM-PICO-Screener 是用于自动化系统综述筛选的轻量 NLP 流水线,基于 Phi-3 Mini 配合 LoRA 与 4-bit 量化,将文章分类为 8 个 PICO 标签。体积约 90 MB,可在消费级 GPU/CPU 上运行,加速生物医学研究中的证据综合。SLM-PICO-Screener is a lightweight NLP pipeline automating systematic review screening. Built on Phi-3 Mini with LoRA & 4-bit quantization, it classifies articles into 8 PICO labels. At ~90 MB, it runs on consumer GPUs/CPU, accelerating evidence synthesis in biomedical research.
0 ★