Evidence Receipt. Related Resources.
Evidence Receipt. Related Resources.
Compared to this week’s papers
Verification pending
Use This Via API or MCP
Signal Canvas is the citation-first public layer for turning one paper into a structured commercialization narrative. Use it to hand off into REST, MCP, Build Loop, and launch-pack execution without losing source lineage.
Use This Via API or MCP
Route this paper proof surface into REST, MCP, or developer workflows while preserving the same evidence receipt and related-resource context.
Page Freshness
Canonical route: /signal-canvas/fame-forecastability-aware-mixture-of-experts-for-heterogeneous-time-series-forecasting
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
Canonical ID fame-forecastability-aware-mixture-of-experts-for-heterogeneous-time-series-forecasting | Route /signal-canvas/fame-forecastability-aware-mixture-of-experts-for-heterogeneous-time-series-forecasting
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/fame-forecastability-aware-mixture-of-experts-for-heterogeneous-time-series-forecastingMCP example
{
"tool": "search_signal_canvas",
"arguments": {
"mode": "paper",
"paper_ref": "fame-forecastability-aware-mixture-of-experts-for-heterogeneous-time-series-forecasting",
"query_text": "Summarize FAME: Forecastability-Aware Mixture of Experts for Heterogeneous Time Series Forecasting"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "FAME: Forecastability-Aware Mixture of Experts for Heterogeneous Time Series Forecasting",
"normalized_query": "2606.08896",
"route": "/signal-canvas/fame-forecastability-aware-mixture-of-experts-for-heterogeneous-time-series-forecasting",
"paper_ref": "fame-forecastability-aware-mixture-of-experts-for-heterogeneous-time-series-forecasting",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Claims: 1
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: FAME: Forecastability-Aware Mixture of Experts for Heterogeneous Time Series Forecasting
PDF: https://arxiv.org/pdf/2606.08896v1
Repository: https://github.com/hit636/FAME
Source count: 4
Coverage: 67%
Last proof check: 2026-06-09T03:27:16.582Z
Signal Canvas receipt window
/buildability/fame-forecastability-aware-mixture-of-experts-for-heterogeneous-time-series-forecasting
Subject: FAME: Forecastability-Aware Mixture of Experts for Heterogeneous Time Series Forecasting
Verdict
Ignore
Preparing verified analysis
Dimensions overall score 0.0
No public code linked for this paper yet.
{"file name": "input.pdf", "number of pages": 10, "author": "Qianyang Li; Xingjun Zhang; Shaoxun Wang; Tao Peng; Jia Wei"
Implication not extracted yet.
partial
Related resources will appear here when this paper maps cleanly to topic, benchmark, or dataset surfaces.
Use an AI coding agent to implement this research.
Lightweight coding agent in your terminal.
Agentic coding tool for terminal workflows.
AI agent mindset installer and workflow scaffolder.
AI-first code editor built on VS Code.
Free, open-source editor by Microsoft.
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Verdict is Ignore because current viability and proof state do not clear the buildability gate.
Time to first demo
Insufficient data
No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.
Structured compute envelope
Insufficient data
No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.
Receipt path
/buildability/fame-forecastability-aware-mixture-of-experts-for-heterogeneous-time-series-forecasting
Paper ref
fame-forecastability-aware-mixture-of-experts-for-heterogeneous-time-series-forecasting
arXiv id
2606.08896
Generated at
2026-06-09T03:27:16.582Z
Evidence freshness
fresh
Last verification
2026-06-09T03:27:16.582Z
Sources
4
References
0
Coverage
67%
Lineage hash
c31d728b8c73e9b1e2f9a3cfc056a188d7e13964cb64b822050f7a1540daf0a3
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
No founder, registry, pilot, or production-adoption signature is attached to this receipt.
Verification
not_verified
Verification is blocked until an external signature is provided.
Pending verification refs / 4 sources / Verification pending
references
proof_status