What's SETRA?
SETRA (Scientific & Economic Trend Research Agent) is an AI-powered system that monitors the intersection of academic research and financial markets, detecting emerging technologies with real market validation.
System Architecture
Collection
arXiv papers, FRED economic data, ETF prices, USPTO patents
Enrichment
Semantic Scholar citations & author data, OpenAlex FWCI & topic mapping
Analysis
Attention Index scoring, field momentum, macro anomaly detection, LLM narrative generation
Output
Dashboard, AI chat (GAME SDK), automated X thread posts
Data Collection
arXiv Papers
Daily automated collection from arXiv API across all categories. Each paper includes title, abstract, authors, categories, publication date, and PDF link. Up to 2,000 papers per query with rate-limited API calls.
Key tracked categories:
Semantic Scholar Enrichment
Papers are enriched via S2 batch API (400 papers/batch) with:
- Citation count, influential citation count, reference count
- TLDR (AI-generated one-sentence summary)
- Author h-index and affiliations
- Citation history (year-by-year breakdown for surge detection)
- DOI (enables OpenAlex lookup)
OpenAlex Enrichment
DOI-based enrichment from OpenAlex (480M+ works corpus) providing:
- FWCI (Field-Weighted Citation Impact) — normalized citation score
- Citation normalized percentile within field
- Topic hierarchy (domain → field → subfield → topic)
- Yearly citation trajectory for trend analysis
Financial & Patent Data
Attention Index (0-115)
A multi-signal score measuring how much academic and market attention a paper is receiving. The score has two parts: a Base Score (0-100) from academic signals, and a Financial Boost (0-15) from market signals. Each academic component is percentile-ranked within the paper's arXiv category.
Base Score (0-100)
Recent citation momentum vs. historical baseline. Detects papers gaining attention rapidly via Semantic Scholar weekly diffs and citation history.
Category-level publication growth blending OpenAlex global corpus data (70%) and local DB growth (30%). Hot field threshold: FMS > 50.
Citation impact using OpenAlex FWCI (Field-Weighted Citation Impact) and citation percentile when available, with category percentile fallback.
Maximum h-index among the paper's authors (via Semantic Scholar), percentile-ranked within category.
Number of highly-cited papers that cite this paper, indicating recognition by key researchers in the field.
Financial Boost (0-15)
When a category-linked theme ETF shows abnormal returns (z-score > 2.0), the paper gets a boost proportional to the anomaly strength.
YoY growth of patent filings in related technology areas (USPTO PatentsView API). 50%+ YoY growth yields the full boost.
Field Momentum Score (FMS) is computed per arXiv category by blending OpenAlex global publication growth (70% weight) with local database publication growth (30% weight). Categories with FMS > 50 are classified as "Hot Fields."
Macro Analysis
Daily macro snapshots aggregate financial data from FRED (12 series) and market sources (28 tickers). SETRA analyzes how macro conditions affect technology sectors, R&D funding, and research activity.
Central Bank Liquidity
- FRB + ECB balance sheets (USD trillions)
- M2 Money Supply (weekly)
- Reverse Repo operations (daily)
- MoM and YoY % changes
Interest Rates & Regime
- Fed Funds Rate
- 10Y / 2Y Treasury yields & yield spread
- CPI and real rate (10Y - CPI)
- Rate regime classification (negative / low / moderate / high real)
- High Yield credit spread (bps)
Market Regime Indicators
- VIX (volatility index) with regime labels
- DXY (US Dollar index) with 1M change
- Copper price (economic activity proxy)
Asset Class Performance
- Equity (VTI), Bonds (AGG), Real Estate (VNQ)
- Commodities (GSG), Gold (GLD)
- YTD and 1-month returns
Innovation Metrics
- US private R&D spending (FRED quarterly)
- Patent velocity (YoY growth by CPC code)
Anomaly Detection
SETRA's 3-layer anomaly system detects: (1) single indicator anomalies (rapid liquidity changes, rate moves), (2) cross-asset patterns (liquidity-rate divergences, equity-bond disconnects), and (3) tech-impact analysis explaining how each anomaly may affect technology sectors and R&D funding.
Automated X Posts
SETRA generates and publishes paper highlight and macro analysis threads to X using Claude (Sonnet) for content generation and Virtuals Protocol GAME SDK for publishing.
Paper Thread (4 tweets)
- Hook — bold opening that stops the scroll
- Data + Explanation — Attention Index, citation surge, what the paper does
- Authors + Forward look — provokes engagement
- PDF link + hashtags (links in thread avoid reach penalty)
Macro Thread (4 tweets)
- Hook — lead with the anomaly or inflection point
- Numbers + Regime — key changes in liquidity, rates, markets
- So What — connect to tech & innovation funding
- Hashtags
Each tweet is capped at 270 characters. Human-like delays (5-15s) between thread tweets. Performance feedback loop: engagement metrics from past posts are injected into prompts to improve future content.
Chat Capabilities
SETRA's chat interface is powered by Virtuals Protocol GAME SDK. The AI agent can query the paper database, analyze macro conditions, and provide research insights in real-time via 7 specialized functions.
search_papersFull-text search on title and abstract with attention threshold filtering
get_paper_detailFull paper details including attention score breakdown and narrative context
get_trending_papersTop papers ranked by Attention Index
get_macro_snapshotLatest macro snapshot with all financial indicators
get_macro_anomaliesRecent anomalies with severity level and tech impact analysis
get_field_statsField momentum scores — filter by hot fields only or see all categories
get_recent_postsSETRA's recent X posts about papers and macro insights
Example questions: "What are the hottest AI papers this week?", "Show me papers with citation surges", "What's the current macro environment?", "Are there any anomalies in the market?"