SCURank: Ranking Multiple Candidate Summaries with Summary Content Units for Enhanced Summarization explores SCURank enhances summarization by ranking candidate summaries based on content units, outperforming traditional metrics and LLM-based methods.. Commercial viability score: 8/10 in LLM Applications.
Use This Via API or MCP
This route is the stable paper-level surface for citations, viability, references, and downstream handoffs. Use it as the proof layer behind Signal Canvas, workspace creation, and launch-pack generation.
Page Freshness
Canonical route: /paper/scurank-ranking-multiple-candidate-summaries-with-summary-content-units-for-enhanced-summarization
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
Canonical ID scurank-ranking-multiple-candidate-summaries-with-summary-content-units-for-enhanced-summarization | Route /paper/scurank-ranking-multiple-candidate-summaries-with-summary-content-units-for-enhanced-summarization
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/scurank-ranking-multiple-candidate-summaries-with-summary-content-units-for-enhanced-summarizationMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.19185"
}
}source_context
{
"surface": "paper",
"mode": "paper",
"query": "SCURank: Ranking Multiple Candidate Summaries with Summary Content Units for Enhanced Summarization",
"normalized_query": "2604.19185",
"route": "/paper/scurank-ranking-multiple-candidate-summaries-with-summary-content-units-for-enhanced-summarization",
"paper_ref": "scurank-ranking-multiple-candidate-summaries-with-summary-content-units-for-enhanced-summarization",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Constellation, claims, and market context stay visible on the paper proof page even when commercialization rails are held back for incomplete proof receipts.
Research neighborhood
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Preparing verified analysis
Dimensions overall score 8.0
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Owned Distribution
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