RTutor 记录了 2,247 月访问量，月度环比增长为 -60.2%，定价为定价请咨询，免费。Semantic Scholar 记录了 8,198,672 月访问量，增长率为 +5.8%，定价为免费。
RTutor is a web app that turns plain-English requests into R (or Python) code, runs it against your uploaded data and returns results plus a downloadable HTML report. Built on large language models such as GPT-4o, it lets analysts upload a CSV, TSV or Excel file and explore distributions, plots, correlations and EDA reports without writing code.
Semantic Scholar is a free, non-commercial academic search engine built by the Allen Institute for AI (Ai2). It indexes more than 240 million papers from every field of science and uses machine learning to extract meaning from abstracts, citations, figures and tables, so researchers find relevant work faster than with keyword-only search.
| 维度 / 指标 | | |
|---|---|---|
| 官方域名 | rtutor.ai | semanticscholar.org |
| 定价模式 | 定价请咨询，免费 | 免费 |
| 月访问量 | 2247 (2,247) | 819.87万 (8,198,672) |
| 月度环比流量变化 | -3401 (-60.2%) | +45.07万 (+5.8%) |
| 主要市场与份额 | 🇺🇸 美国 (57.7%) | 🇺🇸 美国 (22.9%) |
| 直接访问 / 月 | 1193 | 188.44万 |
| 用户评分 | 4 | 4.8 |
| 支持的平台 | 网站 | 网站 |
RTutor is a web app that turns plain-English requests into R (or Python) code, runs it against your uploaded data and returns results plus a downloadable HTML report. Built on large language models such as GPT-4o, it lets analysts upload a CSV, TSV or Excel file and explore distributions, plots, correlations and EDA reports without writing code.
Upload CSV, TSV or Excel files and request analyses in plain English; RTutor generates the R or Python code and executes it for you.
Dedicated tabs for basic, categorical and numerical analysis, summary statistics, tables, correlation and GGpairs plots guide common workflows.
Generate multi-section EDA reports and download them as HTML documents in minutes.
In a session, previous questions and generated code become context, so you can refine charts and clean data conversationally.
Semantic Scholar is a free, non-commercial academic search engine built by the Allen Institute for AI (Ai2). It indexes more than 240 million papers from every field of science and uses machine learning to extract meaning from abstracts, citations, figures and tables, so researchers find relevant work faster than with keyword-only search.
Search 241 million-plus publications from every scientific field using natural-language queries that match meaning rather than exact keywords.
Each indexed paper gets a one-sentence machine-generated TLDR so you can triage results before committing to reading the full text.
An augmented PDF reader that highlights citations, definitions, equations and figures inline, and shows which later papers cited the passage you are reading.
See how a paper was cited, whether citations were influential, and which references shaped the work — useful for literature reviews and citation chasing.
专项更强Broader real-time web search capabilities with academic filters, but less specialized for deep bibliographic citation analysis than Semantic Scholar.
专项更强Broader real-time web search capabilities with academic filters, but less specialized for deep bibliographic citation analysis than Semantic Scholar.
专项更强提供先进的智能引用（Smart Citations）功能以显示论文间的支持或争议关系，但整体索引规模较小。
专项更强提供先进的智能引用（Smart Citations）功能以显示论文间的支持或争议关系，但整体索引规模较小。
专项更强具备优秀的可视化引用收集与文献追踪推荐功能，但缺少行内论文摘要功能。
把问题转化为可信、可治理答案的 agentic 数据分析平台
专项更强提供卓越的学术论文关联可视化图谱对应，但缺乏传统的关键词搜索与全文阅读工具。
与数据对话，获取分析、图表、报告与幻灯片
面向文献综述与可审计系统综述的 AI 原生研究工作台
专项更强Paper Digest is an AI research platform that summarizes literature, generates literature reviews with citations, and delivers daily digests of new papers across arXiv, PubMed, bioRxiv and major conferences. Launched in 2018 and used by millions of researchers, it combines a citation-backed review engine that avoids inventing results with tools for reading PDFs, writing, question answering, claim verification and topic tracking.
专项更强Paper Digest is an AI research platform that summarizes literature, generates literature reviews with citations, and delivers daily digests of new papers across arXiv, PubMed, bioRxiv and major conferences. Launched in 2018 and used by millions of researchers, it combines a citation-backed review engine that avoids inventing results with tools for reading PDFs, writing, question answering, claim verification and topic tracking.
专项更强Organizes research fields into visual concept maps for exploratory discovery, but lacks granular paper recommendation feeds.
专项更强Organizes research fields into visual concept maps for exploratory discovery, but lacks granular paper recommendation feeds.
