Proof pending. This topic has not reached the minimum paper threshold yet.
Topic-specific paper and score movement from the daily diff ledger.
We introduce Target-Event-Agent Networks (TEA Nets) as a computational framework to extract subjects (``Agents"), verbs (``Events"), and objects (``Targets") from texts. Grounded in cognitive network ...
The entropy rate of printed English is famously estimated to be about one bit per character, a benchmark that modern large language models (LLMs) have only recently approached. This entropy rate impli...
This study investigates whether professional translators can reliably identify short stories generated in Italian by artificial intelligence (AI) without prior specialized training. Sixty-nine transla...
Current methods for textual analysis rely on data annotated within predefined ontologies, often embedding human bias within black-box models. Despite achieving near-perfect performance, these approach...
Freshness
Canonical route: /topics
Agent Handoff
Canonical ID text-analysis | Route /topic/text-analysis
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/topic/text-analysisMCP example
{
"tool": "search_papers",
"arguments": {
"query": "Text Analysis",
"cluster": "Text Analysis"
}
}source_context
{
"surface": "topic",
"mode": "topic",
"query": "Text Analysis",
"normalized_query": "text-analysis",
"route": "/topic/text-analysis",
"paper_ref": null,
"topic_slug": "text-analysis",
"benchmark_ref": null,
"dataset_ref": null
}Use This Via API or MCP
Topic pages bundle paper counts, viability trends, author concentration, and top questions into one canonical surface your agents can reference before they open Signal Canvas or create a workspace.