StoryScope: Investigating idiosyncrasies in AI fiction explores A novel pipeline that detects AI-generated fiction by analyzing narrative structure, not just style, offering a robust method for authorship attribution and content verification.. Commercial viability score: 5/10 in AI Content Detection.
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.
Freshness
Canonical route: /paper/storyscope-investigating-idiosyncrasies-in-ai-fiction
Proof data is outside the preferred freshness window.
Proof Quality
One canonical proof ledger now drives the badge, counts, indexing, and commercialization gating.
Commercialization rails stay hidden until proof clears: proof_status, references_count, source_count, coverage.
Search indexing stays off until proof clears: proof_status, references_count, source_count, coverage.
Agent Handoff
Canonical ID storyscope-investigating-idiosyncrasies-in-ai-fiction | Route /paper/storyscope-investigating-idiosyncrasies-in-ai-fiction
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/storyscope-investigating-idiosyncrasies-in-ai-fictionMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.03136"
}
}source_context
{
"surface": "paper",
"mode": "paper",
"query": "StoryScope: Investigating idiosyncrasies in AI fiction",
"normalized_query": "2604.03136",
"route": "/paper/storyscope-investigating-idiosyncrasies-in-ai-fiction",
"paper_ref": "storyscope-investigating-idiosyncrasies-in-ai-fiction",
"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 5.0
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Owned Distribution
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References are not available from the internal index yet.