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Convert PDFs, Word, Excel documents, and images to clean markdown, extract structured data with AI, process invoices with specialized parsing, and search millions of academic papers across PubMed, ArXiv, Google Scholar, and more.

Actions18

Academic → Search

AI-generated

Overview

The node performs academic paper searches across multiple academic databases such as Semantic Scholar, PubMed, ArXiv, Google Scholar, OpenAlex, ERIC, Europe PMC, and Crossref. It merges results from the selected providers based on a user-defined query and supports filtering by publication year, pagination, and selecting specific fields to return. This node is useful for researchers, students, and professionals who want to gather academic literature from various sources in a single search operation.

Use Case Examples

  1. Searching for recent papers on 'deep learning natural language processing' across Semantic Scholar and PubMed, limiting results to 50 and filtering for papers published from 2020 onwards.
  2. Retrieving academic papers on a specific topic with selected fields such as title, authors, abstract, and DOI from multiple providers for comprehensive literature review.

Properties

Name Meaning
Query Search query for academic papers, allowing 1 to 400 characters to specify the topic or keywords to search for.
Providers Selection of academic databases to search, such as Semantic Scholar, PubMed, ArXiv, Google Scholar, OpenAlex, ERIC, Europe PMC, and Crossref. Results are merged across the chosen providers.
Limit Maximum number of results to return, with a range from 1 to 100.
Offset Number of results to skip for pagination purposes, starting from 0.
Year From Filter to include only papers published in or after this year. Leave empty for no filter.
Year To Filter to include only papers published in or before this year. Leave empty for no filter.
Fields to Return Specifies which fields to include in the search results, such as title, authors, year, abstract, DOI, URL, PDF URL, date, total citations, total references, provider, provider URL, and raw provider-specific metadata.

Output

JSON

  • title - Title of the academic paper.
  • authors - Authors of the paper.
  • year - Publication year of the paper.
  • abstract - Abstract or summary of the paper.
  • doi - Digital Object Identifier for the paper.
  • url - URL link to the paper.
  • pdfURL - URL link to the PDF version of the paper.
  • date - Date of publication.
  • totalCitations - Total number of citations the paper has received.
  • totalReferences - Total number of references cited by the paper.
  • provider - Name of the academic data provider.
  • providerURL - URL of the academic data provider.
  • providerData - Raw metadata specific to the provider.

Dependencies

  • An API key credential for the PDF Vector API

Troubleshooting

  • Common issues may include invalid or missing API credentials, resulting in authentication errors.
  • Exceeding the maximum allowed limit for results (more than 100) may cause errors; ensure the limit is within the allowed range.
  • Incorrect or empty query strings may return no results or errors; ensure the query is valid and non-empty.
  • Network or API service issues may cause request failures; check connectivity and API service status.

Links

Discussion